Table of Content

07 February 2024, Volume 38 Issue 1 Previous Issue   

Special Column on "Modeling and Structural Design of Tire Mechanics Characteristics."

Select

Summary of research on rolling resistance of vehicle tires 2024, 38 (1):  1-8.  Abstract ( 309 )   PDF (1242KB) ( 841 )   Save As one of the tire mechanical properties, the steady rolling resistance of automobile tire exerts significant impacts on the power performance, fuel economy, braking performance, handling stability and tire lifespan. In this paper, the mechanism of tire rolling resistance is described, and the experimental measurement, numerical simulation and theoretical calculation methods of tire rolling resistance are summarized. Then, the influence of wheel structure parameters and material properties on tire rolling resistance is analyzed. Finally, the technical challenges and development trend of tire rolling resistance research are presented. This paper may provide some reference for the research of tire rolling resistance. Related Articles | Metrics

Select

Research on the hydroplaning performance of tire tread groove based on fluid-structure coupling 2024, 38 (1):  9-19.  Abstract ( 169 )   PDF (5397KB) ( 141 )   Save  In this paper, the 205/55 R16 tire is used as the research object. Based on the Abaqus CEL fluid-structure coupling method, the finite element model of tire hydroplaning is built. The tire vertical stiffness generated from the simulation is compared with the experimental data. While validating the reliability of the tire model, the optimized Eulerian domain helps better capture and analyze the water flow characteristics during tire hydroplaning. The hydroplaning critical velocity generated by NASA empirical equations is employed to verify the reliability of the tire hydroplaning model. The impacts of different inflation pressure and water film thickness on the tire hydroplaning performance are analyzed. The tire tread structure is optimized by introducing a V-shaped transverse tread pattern and adding an F1 Nose structure. The validity of the optimized tread groove sub-model is verified, and then the hydroplaning critical velocity and water flow pressure of the tire before and after the optimization are compared. Results show our optimized method effectively improves tires’ hydroplaning performances. Related Articles | Metrics

Select

An investigation of tire equivalent model and efficient computation 2024, 38 (1):  20-29.  Abstract ( 125 )   PDF (4405KB) ( 125 )   Save The intricate tire structure and hyperelastic materials such as rubber significantly impact the accuracy and computational speed of finite element models for tires. This stands as a crucial consideration in the tire modeling process. To ensure rapid computation of the finite element model for tires after matching with the entire vehicle, an exploration of simplified finite element model approaches is conducted. This involves constructing a linear material-based finite element model for tires and achieving equivalent processing of the model. Constructing a detailed finite element model for tires, conducting simulation analyses of stiffness characteristics and ground interaction properties, and validating the effectiveness of the detailed model through experimental and simulation comparisons. Three simplification approaches are proposed for the detailed tire model: solid element modeling, a hybrid model combining solid and shell elements, and a hybrid model combining solid and beam elements. Linearization of nonlinear materials is applied to these models. The inflation-induced lateral deformation, inflation-induced radial deformation, and radial load indentation are calculated using linear materials for the three equivalent models. Sensitivity analysis of material parameters based on deformation is conducted to obtain the optimal equivalent model. The results indicate that the equivalent model’s ground contact imprint and ground pressure, when compared with the detailed model, exhibit deviations within acceptable limits, confirming the accuracy of the equivalent model. The comparison of computational time between the equivalent model and the detailed model verifies a noticeable improvement in computational efficiency for the equivalent model. Furthermore, the feasibility of substituting the equivalent model for the detailed model is confirmed through a comparison of various modal orders between the two models. The proposed equivalent model provides a simplified approach for complex tire finite element simulations, offering a modeling simplification strategy. It serves as a tire modeling method for overall vehicle finite element simulations. Related Articles | Metrics

Select

Tire rolling resistance estimation algorithm based on acceleration signal 2024, 38 (1):  30-40.  Abstract ( 140 )   PDF (2664KB) ( 243 )   Save Tire rolling resistance is an important factor affecting vehicle fuel economy, which is mainly due to the energy loss caused by the hysteresis effect of rubber materials. For passenger cars using radial tires, about 3.4% to 6.6% of fuel consumption is used to overcome tire rolling resistance, so the topic of reducing vehicle fuel consumption by reducing tire rolling resistance has received more and more attention from scholars. The purpose of this paper is to establish a more accurate and effective tire rolling resistance prediction model by using acceleration signal combined with intelligent tire technology. In this paper, the 205/55/R16 passenger car radial tire is taken as the research object. Firstly, based on the contribution rate of rolling resistance, the structure of the radial tire is simplified reasonably, and the finite element model of the tire is established by ABAQUS finite element simulation software and material parameterization method. The UAMP subroutine tire is used to control the angular velocity of the tire to obtain the steady-state free rolling angular velocity of the tire and extract the rolling resistance data. Through finite element analysis and control variable method, the rolling resistance of tire finite element model under variable load, vehicle speed and tire pressure is studied. The validity of the finite element model is verified by the stress and strain characteristics of tire joints. Secondly, the acceleration data of the nodes at the central axis of the tire lining under various compound working conditions are extracted, and the acceleration of the nodes is converted from the body coordinate system to the acceleration body coordinate system using the coordinate transformation matrix, and the longitudinal, lateral and vertical acceleration curves are obtained. Comparing the response degree of different signals to rolling resistance, the longitudinal and vertical acceleration signals are selected as the observation signals. The generation mechanism of tire rolling resistance is analyzed. Yule-Walker frequency domain analysis method is used to calculate the power spectral density of acceleration signals. The relationship between signal power and frequency is estimated through the correlation of signals. Combined with tire pressure, vehicle speed and load, a tire rolling resistance estimation model based on partial least squares regression algorithm is built. Finally, the fitting effect of the model can be approximated according to the estimation results of the model under 20 test conditions of variable load, vehicle speed and tire pressure. The mean square error of the tire rolling resistance estimation algorithm based on acceleration signal is 0.318 3, and the goodnessof fit is 0.967 6. Under the same data set, the mean square error and goodness of fit of the tire rolling resistance estimation algorithm, which only uses vehicle speed, tire pressure and load as input variables, are 0.352 4 and 0.941 9. The results show that compared with the traditional physical model of rolling resistance, the fitting effect of the regression equation combining the tire acceleration signal and driving parameters is better than that of using only the driving parameters, and the prediction result is more accurate, which may provide some references for the research of rolling resistance. Related Articles | Metrics

Vehicle engineering

Select

Design of PSO-LQR controller for trailer steering of tractor semitrailers 2024, 38 (1):  41-49.  Abstract ( 133 )   PDF (3182KB) ( 172 )   Save To address the poor tracking performance of semitrailers when tractors steering at low speeds, an active steering Linear Quadratic Regulator (LQR) based on Particle Swarm Optimization (PSO) is designed, and the impact of different weight matrix acquisition methods on the steering control effect of trailers is explored. First, the reliability of the kinematics model of the tractor-semitrailer with the trailer steering system is verified. Second, an LQR for low-speed trajectory tracking of the trailer is designed, and the weight matrix in the LQR is optimized by employing PSO algorithm. Finally, the controller performance with different weight matrix acquired by different methods is studied. Research results show the LQR controller optimized by PSO algorithm allows the trailer to enter a stable tracking state faster; when the weight matrix R is set to 0.1 and 1, compared to the trailer tracking error corresponding to the manually adjusted weight matrix Q, the trailer tracking error corresponding to the global optimal weight matrix is down by 26.1% and 19.4% respectively in a single U-shaped path, and down by 40.9% and 43.4% respectively in a spiral path on the ramp. Related Articles | Metrics

Select

Research on actuated control of intersection considering utilization rate of traffic direction 2024, 38 (1):  50-58.  Abstract ( 108 )   PDF (2572KB) ( 133 )   Save The intersection delay accounts for a large proportion in the urban travel delays. To improve the traffic efficiency at intersections, this paper takes the standard four-phase intersection as the research object and proposes an actuated traffic direction utilization signal control method based on the real-time road condition information at intersections. According to the vehicle space occupancy rate, the traffic efficiency at intersections, and the threshold of the head-to-head distance, an optimized model of the intersection phase decision-making is built in python. An intersection with wild fluctuations in traffic flow in Changsha is taken as an example. Through vissim 8.0 modeling, the actuated control method and the traditional webster control method based on traffic flow are simulated and compared under various traffic flows. Our research results show the average vehicle delay at the intersection decreases by 3.21%, 13.1%, and 4.17% at off-peak, PHF15, and congested traffic periods; the reduction rate of the average vehicle delays at the intersection will increase first and then decrease with the continuously growing traffic. Our research results confirm the actuated control readily adapts to a wide range of traffic conditions and effectively reduces vehicle delays at intersections. Related Articles | Metrics

Select

Research on image de-raining method based on improved diffusion model 2024, 38 (1):  59-66.  Abstract ( 256 )   PDF (4031KB) ( 279 )   Save To address the excessive rain removal and poor generalization of images, this paper proposes a single-image de-raining method by improving diffusion model. The data becomes Gaussian distribution by adding Gaussian noise to the forward process. The dual input information channels of the residual module are designed and the ECA (Efficient Channel Attention) channel attention mechanism module is added to build a noise estimation network. Thus, a global average pooling without reducing the dimension is achieved and the local cross-channel interaction information is captured. The model network is employed to reverse sampling, predict the noise as a rain mark and remove it, and thus achieve image de-raining. By employing simulated raindrop datasets and the Rain100 dataset, comparative experiments are conducted to compare our improved diffusion model with other four algorithms. The experimental results demonstrate our improved diffusion model effectively removes rain streaks, with peak signal-to-noise ratios of 30.328 5 for raindrops and 34.896 5 for rain lines, and structural similarities of 0.927 1 and 0.962 0 respectively. A real rain image dataset is built, and the YOLOv7 algorithm is employed to perform vehicle detection on the rain-removed images. Our results show the improved diffusion model for rain removal effectively enhances the confidence of vehicle detection, further confirming it has outstanding de-raining performance and generalization capability. Related Articles | Metrics

Select

The modified velocity prediction strategy based on the collision risk clustering in cut-in scenarios 2024, 38 (1):  67-76.  Abstract ( 130 )   PDF (3889KB) ( 207 )   Save High-precision vehicle speed prediction in cut-in scenarios is the key to ensuring the safety of autonomous driving cut-ins. To improve the safety of autonomous driving vehicles in cut-in scenarios, this paper studies the high-precision prediction method of ego-vehicle speed in cut-in scenarios based on vehicle-vehicle coupling risk clustering. First, the vehicle cut-in and cut-out segments are extracted based on the natural driving data obtained from the experiments, and the clustering analysis is performed based on the collision risks and acceleration correlation features using the K-means method. Second, based on the support vector machine (SVM) model, the online classification of vehicle-vehicle interaction state of cut-in and cut-out conditions is performed, and the real-time prediction of dangerous cut-in conditions is made. Finally, an improved vehicle speed prediction method based on ARIMA model (Autoregressive Integrated Moving Averaged Model) is proposed, optimizing real-time vehicle speed with online recognition results. Simulation results show the improved ARIMA vehicle speed prediction based on collision risk clustering significantly improves cut-in safety, cutting the vehicle collision risks by 10%～20% when compared to the traditional prediction methods. Our research may provide some references for improving the cut-in safety of autonomous driving vehicles. Related Articles | Metrics

Select

Design and crashworthiness of bionic longitudinal mixed negative Poisson’s ratio structure 2024, 38 (1):  77-86.  Abstract ( 137 )   PDF (4377KB) ( 209 )   Save To improve the crash-resistance of the protective structure in the automobile structures, 24 energy absorption structures with bionic mixed negative Poisson’s ratio are designed by extracting the microstructure of the crayfish claw through biological experiments. Mass specific energy absorption (SEA), structural average crushing efficiency (CFE), and initial peak load (IPF) are taken as the main indexes to evaluate the crashworthiness of the structure. The validated finite element model is employed to simulate the design structure, and the key parameter a (depth of intracavity) affecting the crashworthiness of the structure is determined through the analysis of the final data. The optimal crashworthiness structure is selected by weighted combination comprehensive evaluation method according to actual working conditions. The results show when a=6.80 mm, the BCDA hybrid structure achieves the best crashworthiness, SEA=3.21 kJ/kg, IPF=8.58 kN, CFE=31.29% after optimization. Compared with the single cell structure, the optimized hybrid model decreases the IPF by 35.24% at most, increases the SEA by 35.72%, and decreases CFE by 47.20% at most. Our study may point a new direction for the design of energy absorption structures with negative Poisson’s ratio. Related Articles | Metrics

Select

Research on driving style of expressway ramp entrance section 2024, 38 (1):  87-95.  Abstract ( 97 )   PDF (2534KB) ( 98 )   Save To analyze the driving style of drivers at the on-ramp junction of the expressway, this paper employs the NGSIM dataset. To ensure the accuracy of data, spatiotemporal constraints are set to eliminate abnormal data and the smoothed trajectory data in on-ramp merging area are obtained. First, factor analysis (FA) method is employed to reduce the dimensionality of the original multidimensional features and five major factors well represented in the driving style are obtained. Second, the K-means algorithm is used to cluster the principal factors and three driving styles are identified: cautious, prudent and aggressive driving. The recognition results before and after FA are compared. Our results show in aggressive driving, continuous lane-change within a short period of time and the smaller headway during the whole ramp merging process are more likely to occur. Related Articles | Metrics

Select

Aeroacoustic optimization and experiment of hollow mirror handle 2024, 38 (1):  96-102.  Abstract ( 97 )   PDF (3878KB) ( 71 )   Save To better reflect the styling of the rearview mirrors, a domestic brand adopts an unconventional hollow mirror handle design in its new vehicle development. This paper studies and optimizes the aerodynamic characteristics of the rearview mirror handle by simulation and wind tunnel test to reduce the acoustic response in the vehicle’s driver’s cockpit. Our simulation reveals a serious airflow separation in the original mirror handle molding, accompanied by serious swirling vortex, which create unfavorable wind noises. To address the problem, this paper proposes two optimized schemes which effectively improve the velocity distribution gradient and airflow separation at the mirror handle. Our experimental results show the two optimized schemes substantially enhance the sound pressure level and speech clarity. The interior sound pressure level is reduced by 0.18 dBA and 0.21 dBA respectively, and both articulation indexes are improved by 1.5%. Meanwhile, the acoustic microphone array imaging is employed to accurately locate the component in which the roar occurs and the corresponding frequency band. By optimizing the surface roughness scheme, the contribution of the second optimized scheme is further increased by 0.02 dBA and 0.6%. Our research results validate the credibility of the simulation method in the project development process and provide some references for the design and optimization of the hollow mirror handles of rearview mirrors. Related Articles | Metrics

Select

Lightweight design of electric vehicle battery box 2024, 38 (1):  103-109.  Abstract ( 127 )   PDF (1913KB) ( 93 )   Save As the battery box goes lightweight, suitable lightweight materials are selected to match the panels at different positions of the battery box and take full advantage of material properties. In this paper, the TOPSIS method based on CRITIC weight and orthogonal test is employed. First, the decision-making matrix of the properties of commonly used metal materials in battery boxes is built, and the TOPSIS method based on CRITIC weight is employed to standardize the processing, eliminate the dimensional differences of different groups of data, determine the objective weight of each group of data, calculate the relative fit of each scheme, and select alternative materials. Then, the orthogonal experimental design and range analysis are employed to match the alternative materials with different plates in the battery box, and a multi-material battery box is created. Finally, the size of the multi-material battery box is optimized. The optimized battery box model reduces weight by 5.3 kg with a weight reduction rate of 11.37% while meeting the requirements of strength, stiffness and low-order mode frequency. Related Articles | Metrics

Information and computer science

Select

Particle swarm algorithm improved by hybrid strategies 2024, 38 (1):  110-121.  Abstract ( 150 )   PDF (5678KB) ( 227 )   Save To remedy the defects of particle swarm algorithms, including the local optimum, low convergence accuracy, and slow convergence speed, this paper proposes an improved particle swarm algorithm based on hybrid strategies. First, the population is initialized by the fusion Circle mapping and the elite reverse learning to improve its quality and accelerate the convergence. Second, the spider mobile strategy is introduced in the particle speed update to balance the local and global search of the algorithm; then self-adaptive T distribution is proposed to enhance the algorithm’s global search and its ability to jump out of local optimum. Finally, the 15 single-peak and multi-peak functions are simulated and analyzed with the other three algorithms. Our results show the improved algorithm possesses strong optimizing capacity and stability. Related Articles | Metrics

Select

A denoising-attention based Zero-DCE for tunnel image enhancement 2024, 38 (1):  122-130.  Abstract ( 170 )   PDF (3520KB) ( 347 )   Save Tunnel images, affected by the shooting environment, suffer from uneven illumination distribution, local occlusion, and many noises. To address the problems of overexposure and distortion in existing image enhancement algorithms, this paper proposes a tunnel image enhancement algorithm called DA-Zero-DCE (Denoising-Attention based Zero-Reference Deep Curve Estimation). First, based on the Zero-DCE model, the U-Net is employed to improve the backbone network DCE-Net for curve estimation, and a coordinate attention mechanism is added to enhance the dark light perception ability of local image areas. Second, the NAF-Net noise removal module is added after the curve estimation backbone network to effectively suppress the noises after low-light enhancement by Zero-DCE. To offset the distortion and overexposure of the enhanced images, the 4-neighborhood calculation method of the spatial consistency loss function is extended to an 8-neighborhood calculation method, enhancing the smoothness of the outputs. Through the ablation experiment on the LOL dataset, the DA-Zero-DCE model, compared to the Zero-DCE model, improves PSNR by 10 dB and SSIM by 0.1, demonstrating its feasibility and effectiveness. Related Articles | Metrics

Select

Data dimensionality reduction and clustering quality evaluation of K-means clustering 2024, 38 (1):  131-141.  Abstract ( 131 )   PDF (3310KB) ( 107 )   Save Related Articles | Metrics

Select

Study on ECG classification algorithm based on improved U-Net network 2024, 38 (1):  142-149.  Abstract ( 136 )   PDF (1416KB) ( 143 )   Save  Cardiovascular disease, with the highest mortality rate across the globe, kills over ten million people every year. Thanks to the continuous development of artificial intelligence, patients’ heart conditions can now be quickly and accurately diagnosed with the assistance of automatic electrocardiogram anomaly classification technology. This paper proposes an electrocardiogram classification algorithm based on CPSC-2018 twelve lead data, which combines U-Net network and attention mechanism. First, the data are processed for equal length and normalization to address their varied lengths. Then, the preprocessed data with longer lengths are reprocessed by the skip layer connection and encoding and decoding methods in the U-Net network. An attention mechanism is added to the last layer of U-Net network decoding to combat noise and improve the effective information attention and accuracy of the model. Finally, CPSC-2018 dataset is employed to verify the model. Our experimental results show the proposed model delivers fairly satisfying classification performance, recording its accuracy, recall, and F1 values of over 90% in identifying atrial fibrillation (AF) and right bundle branch block (RBBB) arrhythmias, and an average F1 value of 82.5%. Related Articles | Metrics

Select

Hybrid similarity metric for instrument quotation spreadsheet structure recognition 2024, 38 (1):  150-159.  Abstract ( 77 )   PDF (2784KB) ( 76 )   Save For instrumentation companies, it is of great significance to quickly and efficiently automate the response to users’ request for quotation and to realize unmanned quotation. Nevertheless, there is no unified and standardized format for the bill of materials spreadsheets provided by different users, resulting in semi-structured quotation spreadsheets for instrumentation companies and creating difficulties for unmanned quotation systems to perform analysis. The key to building an unmanned quotation system is to accurately automate the extraction of meter parameters, which presupposes a proper understanding of the spreadsheet structure. Therefore, with the goal of building an unmanned quotation system, this paper studies the structure recognition of instrument quotation spreadsheets and proposes hybrid similarity metrics for table structure recognition (HSMTSR). With Levenshtein distance, Dice coefficient and cell type similarity (TySim), this approach identifies spreadsheet structures based on the similarity resolution of cell and row data. Meanwhile, flowmeter spreadsheet dataset (FSDS) is built to analyze the structure of meter quotation spreadsheet, including 714 spreadsheets with 8 574 rows of data. Practical applications show the method accurately and efficiently automates the identification of multiple complex structures of instrument quotation spreadsheets, and achieves superior results in several evaluation metrics. Related Articles | Metrics

Select

Research on air compressor load prediction and intelligent scheduling algorithm 2024, 38 (1):  160-168.  Abstract ( 152 )   PDF (1584KB) ( 163 )   Save The air compressor system consists of multiple units, and the optimization of unit combination is a nonlinear and large-scale task of multiple objectives and constraints. To address such problems as high energy consumption and serious waste of resources in air compressor scheduling, this paper studies the quantity scheduling problem of air compressors based on the characteristics of air compressor combination. A multi-strategy improved Harris Hawk Optimization Algorithm (MHHO) combined with Deep Echo State Network (DESN) is proposed to predict the load of the air compressor. After obtaining the load required for 24 hours a day, the MHHO algorithm is employed for unit combination scheduling and gas consumption allocation. Our experimental results show the prediction model achieves a higher prediction accuracy, and thus is highly applicable for air compressor load prediction. Intelligent scheduling improves the unit operation efficiency and reduces the system’s energy consumption. Related Articles | Metrics

Select

Research on multimodal hate meme recognition based on graph convolutional network 2024, 38 (1):  169-179.  Abstract ( 151 )   PDF (2339KB) ( 171 )   Save Memes exist in the form of images and texts and are used to describe hate speeches, rumors that spread among users on the Internet. They often use web entities such as popular figures, events, or historical figures to express hate emotions. These implicit emotional expressions are worth academic attention, but web entities are mostly ignored by existing meme identification methods. To address the problem, this paper proposes a meme recognition method based on graph convolutional network. Specifically, the web entity information contained in the image is first extracted. The web entity modality and the text modality are fused by a graph convolutional network. An external dictionary is employed to measure the relationship between the web entity and the meme text from multiple perspectives when building cross-domain graph. Then, the text and image modalities are interacted through the attention module. Finally, the self-distillation technology is employed to improve the model’s information utilization rate. Our experimental results on the Hateful Memes dataset and the MAMI dataset reach an accuracy of 76.03% and 73.9% respectively, and the performance is superior to the existing SOTA model. Related Articles | Metrics

Select

Optimization method for signal control scheme considering unbalanced traffic flow with the effect of non- motorized vehicles 2024, 38 (1):  180-191.  Abstract ( 98 )   PDF (2527KB) ( 75 )   Save The current design of intersection signal phase relies heavily on practical experience. Without thorough consideration of the impact of the non-traffic flow characteristics and non-motorized vehicles’ street-crossing mode, it often causes poor use of time and space resources. This paper proposes an intersection signal dynamic release scheme which takes into account the phase traffic flow imbalance and the impacts of non-motorized vehicle expansion effect on motorized vehicles. A delay estimation model based on different release methods is built, and a sensitivity analysis method is employed to present quantitative setting conditions for different release schemes. An intersection in Beijing is taken as an example. The signal timing schemes corresponding to different release schemes are obtained by improving the ant colony algorithm. The results show “rotation release+twice crossing” is used when aj is greater than 0.25. When aj is less than 0.25, the ratio of left-turn and direct flow is greater than 1∶3, and the left-turn flow of non-motorized vehicles is 100～500 veh·h-1, “symmetrical release + once crossing” is adopted. When the ratio of flow is less than 1∶3, “symmetrical release + twice crossing” is adopted accordingly. Compared to the traditional release scheme, the use of symmetrical lap release results in a reduction of 13.6s in delay per person, down by 25.81%. Therefore, the release scheme proposed in this paper effectively improves the traffic efficiency at intersections. Related Articles | Metrics

Select

Consistency and circular formation control of multi-agent system 2024, 38 (1):  192-200.  Abstract ( 125 )   PDF (2426KB) ( 174 )   Save In this paper, a hybrid distributed controllers is proposed for the circular formation control of a group of multi-agent systems with constant and non-identical speeds. The controller consists of two parts, one part acts on the phase of the system and the other part acts on the angular frequency, in which the controller on the angular frequency mainly coordinates the influence of the phase change and the initial angular frequency on the stability of the system. The formation design is mainly based on the phase control of the system. In this paper, two formation design schemes are given, namely, position-based approach and displacement-based approach. The agent position-based approach can perceive its expected center position in real time and converge to the corresponding expected position when a formation develops. The agent displacement-based approach needs to perceive the relative displacement between itself and its neighbors in real time, and then converge to the difference of the expected center position between itself and its neighbors. The research results show that the hybrid controller drives the agents to gradually form a desired circular formation at the specified angular frequency when the agents with constant and non-identical speeds in any initial state, and the phases of all agents are synchronous or balanced, and their angular frequencies are asymptotically synchronized and converged to the specified value. The simulation of a system composed of five agents shows the four-cycle motion trajectory intercepted is consistently circular, and the error between the simulated center position and the expected center position based on the position method is below 0.01, the error between the relative displacement and the expected displacement based on the displacement method is below 0.000 2, demonstrating the accuracy and effectiveness of the formation control scheme. Related Articles | Metrics

Machinery and materials

Select

Optimization of multi-objective performance of recycled brick aggregate concrete for road applications in cold regions 2024, 38 (1):  201-211.  Abstract ( 71 )   PDF (4900KB) ( 100 )   Save Abandoned clay bricks as recycled aggregates in concrete can effectively mitigate the environmental pollution caused by construction waste. By taking 5-10mm and 10～20 mm recycled brick aggregates as independent variables and water-cement ratio as a factor, the road performance parameters such as compressive strength, abrasion resistance, and frost resistance are considered as objectives. The impacts of various factors are determined by applying a central composite experimental design. The experimental results are regressed and a fitting model is proposed to describe the relationship between the factors and the road performance of concrete. The reliability and stability of the model are validated through variance analysis. A thorough analysis of the model is performed using a response surface 3D plot to determine the impact of the factors on the three road performance parameters of recycled brick aggregate concrete in cold regions. The influencing factors are ranked from high to low as follows: water-cement ratio, 10～20 mm brick aggregate, and 5～10 mm brick aggregate. Optimizing the road performance of cold region regenerated brick aggregate concrete involves meeting three requirements for cold region road conditions: maximizing compressive strength and frost resistance, maximizing wear resistance while maintaining excellent compressive strength and frost resistance, and emphasizing frost resistance based on assigned weights. The results show the proposed fitting model can be used to obtain the optimal mixture ratio based on engineering objectives, optimizing the preparation process of recycled brick aggregate concrete and providing a theoretical reference for its practical application in engineering fields. Related Articles | Metrics

Select

Study on the preparation and performance of horizontal borehole grouting material for airport pavement 2024, 38 (1):  212-220.  Abstract ( 82 )   PDF (3673KB) ( 102 )   Save To satisfy the material requirements of the horizontal grouting project at airports with non-stop flights, compound silicate cement and sulfo-aluminate cement compounding tests are conducted. The silicate-sulfur aluminate composite cement mortar meeting the construction requirements is prepared in many experiments, and the setting time, fluidity, 1d compressive strength of the materials are studied with the help of such equipment as Vicatometer, truncated cone circular mold and pressure testing machine. The results show a higher proportion of sulfo-aluminate cement has a shorter setting time; the water-cement ratio and water-reducing agent admixture exert a greater impact on fluidity and have some influences on other properties. With the best ratio confirmed, the results of drilling and grouting simulated by cylindrical strength specimen and field test section with HWD and ground penetrating radar show the composite cement mortar possesses satisfying properties, and the strength and structure of road surface are restored to the level before drilling, fully meeting the construction requirements at airports with non-stop flights. Related Articles | Metrics

Select

Determination and analysis of TTT curve of 38MnVTi non-quenched and tempered steel 2024, 38 (1):  221-228.  Abstract ( 90 )   PDF (4060KB) ( 135 )   Save  This paper studies austenite transformation products of 38MnVTi non-quenched and tempered steel during isothermal cooling and the relations between transformation amount and time. The expansion curves of different isothermal temperatures are obtained by Gleeble-1 500D thermal simulation tester. The expansion curves at different isothermal temperatures are acquired by expansion method on Gleeble-1 500D thermal simulation testing machine. The isothermal transformation curve (TTT curve) of 38MnVTi non-quenched and tempered steel is calculated and fitted by Origin software. Our results show the precipitation temperature of cementite is 750 ℃, the ferrite precipitation temperature 840 ℃, the martensite precipitation temperature 360 ℃ and the martensite transformation termination temperature 212 ℃. Under the isothermal cooling conditions of 540, 510, 480 and 430 ℃, the maximum transformation amounts of bainite are 16.9%, 26.8%, 38.5% and 55.3%, respectively. Related Articles | Metrics

Select

Study on multiphase flow coupling model of aircraft deicing impact jet 2024, 38 (1):  229-236.  Abstract ( 93 )   PDF (3676KB) ( 275 )   Save This paper studies the modeling and numerical simulation of the impact jet and impact wall in aircraft deicing spray operations, and analyzes the velocity and pressure distribution characteristics of the impact wall. The phase field function φ is employed to explain the jet deflection phenomenon simulated by the phase field and level set models. The reason for the uneven pressure distribution gradient around the impact jet is explored, and the simulation results of different multiphase flow numerical models are compared based on the Realizable k-ε turbulence model. Our research results show the cross-section of the impact jet develops conically along the central axis, with the flow velocity rapidly decreasing to zero at the stagnation point and the pressure reaching its maximum value. The wall jet gradually gains maximum flow velocity when it deviates from the stagnation point by 0.15～0.2 m. The simulation results of different multiphase flow models are compared with the commonly used turbulence coefficient in experiments. Considering the velocity, pressure distribution characteristics and jet turbulence coefficients simulated by the models, it is concluded that the mixture model and the phase-transfer mixing model are more suitable for the study of aircraft deicing jets and other similar large-flow, multi-fluid microcluster-like flows. Related Articles | Metrics

Select

Application of multi-objective PSO algorithm based on Pareto control in milling parameter optimization 2024, 38 (1):  237-247.  Abstract ( 94 )   PDF (3931KB) ( 134 )   Save Process parameters are key factors affecting the quality and efficiency of part processing, and optimizing and adjusting process parameters is the most effective way to improve the processing technology. In this paper, a multi-objective cutting parameter optimization method based on application examples is proposed for the optimization of milling processing parameters. First, a unified mathematical model for multi-objective optimization of cutting process parameters is built, with material removal rate, cutting force, and tool life as objective functions. Second, the objective functions are combined by employing cutting data. A mathematical model of the problem is built, and applicable solutions are investigated to obtain the optimal one. The effectiveness of parameter optimization is verified through experiments. The proposed method may provide some references for the selection of machining parameters. Related Articles | Metrics

Select

Research on self-diagnostic measurement method of absolute circular time-grating eccentricity state 2024, 38 (1):  248-254.  Abstract ( 75 )   PDF (3385KB) ( 127 )   Save To address the problem that the measurement accuracy of the circular time-grating sensor is adversely affected by the large first harmonic wave error due to the non-concentricity of the stator and rotor during the installation process, this paper proposes a self-diagnostic measurement method of the absolute circular time-grating eccentric state based on the multi-reading heads structure. In this structure, a single reading-head and four independent reading-heads are respectively arranged in the inner and outer rings of the circular time-grating rotor. According to the phase comparison relationship between the inner and outer ring induction signals, the degree of sensor eccentricity is assessed to realize the self-diagnostic measurement function of the sensor under the eccentric state. The measuring system built by LabVIEW simultaneously processes the phase meter values of the single induction signal in the inner ring and the four induction signals in the outer ring, obtains the absolute position information of the sensor and displays the absolute angular displacement value. Our experimental results show the measurement error accuracy of the sensor prototype is ±1″ in the whole week after the adjustment and installation, substantially improving the measurement accuracy of the sensor. Related Articles | Metrics

Energy, power and environment

Select

Research on modeling and correction method of gas-liquid two-phase lithium-ion battery in thermal runaway state 2024, 38 (1):  255-263.  Abstract ( 162 )   PDF (2609KB) ( 142 )   Save Lithium-ion batteries, which are widely used energy storage devices in modern electronic devices and electric vehicles, have been identified as a key component in the transition from depleted fossil fuels to sustainable energy production and use worldwide. However, due to misuse and improper use, lithium-ion batteries can experience thermal runaway, a phenomenon that manifests itself as a significant build-up of gases within the battery. Traditional solid-liquid two-phase models present challenges in characterizing the complexity of thermal runaway mechanisms. In order to understand the mechanism of thermal runaway more accurately, an electrochemical-thermal coupling model of 18650 lithium-ion battery pack is built based on gas-liquid two-phase flow, and the variation law of internal stress, temperature and electrolyte concentration of lithium-ion battery during thermal runaway is well studied. According to the chemical reaction process and the dynamic evolution of internal pressure and temperature, the whole thermal runaway process is divided into reaction stage, diffusion stage and equilibrium stage, so that the characteristics of each stage can be studied in more detail. The effectiveness of the theoretical analysis is verified by using the COMSOL Multiphysics 5.5 software, and the theoretical model is modified, and the results of the comparative analysis show the importance and complementarity of the theoretical analysis and simulation experiments in the study of thermal runaway of lithium-ion batteries. The difference between the peak value of the internal stress correction value and the simulated value is only 0.04 MPa, the error is significantly reduced, and the accuracy is increased by 80%, which indicates that the model can more accurately describe the thermal runaway process of lithium-ion battery, highlighting the accuracy enhancement obtained by this modeling method. Our study also reveals that the thermal runaway gas can cause a drastic change in the internal temperature of the battery, and the amplitude of the change is basically synchronized with the increase of the internal pressure of the battery, the thermal runaway occurs at a temperature of 60 ℃, and the thermal runaway gas is ignited when the internal temperature rises to 160 ℃, and the maximum simulated temperature and corrected temperature are 177 ℃ and 172 ℃ at 640 seconds, respectively. The formation of hot spots is the main cause of uneven temperature distribution within the battery. In addition, Our study shows that the electrolyte concentration decreases from 1 200 mol/m3 to 837 mol/m3 simultaneously from the theoretical and simulated values of the electrolyte concentration caused by the thermal runaway gas throughout the thermal runaway process. This dynamic evolution trend accelerates the formation of gas-liquid two-phase flow and the process of thermal runaway, forming gas-liquid two-phase flow, the interaction between the electrolyte and the electrode material, which leads to the reduction of the electrolyte concentration to a large extent. The electrochemical-thermal coupling model based on gas-liquid two-phase flow and the in-depth study of the thermal runaway process deepens our understanding of the mechanism of thermal runaway of lithium-ion batteries, and provides a more in-depth theoretical basis for preventing or remedying the thermal runaway problem of lithium-ion batteries. Related Articles | Metrics

Select

Secondary control of island microgrid based on distributed consensus algorithm 2024, 38 (1):  264-272.  Abstract ( 108 )   PDF (2802KB) ( 126 )   Save In the distributed generator parallel system of island microgrid, when droop control is adopted, the output reactive power of power supply cannot be distributed according to capacity due to the mismatch of line impedance. Based on the droop control, this paper proposes a distributed secondary control strategy, employing a consensus algorithm to adjust the virtual impedance value. The proposed strategy obtains the reactive power difference between distributed generations through the consistency algorithm, inputs it into a proportional integral controller to obtain the virtual impedance correction value, and realizes the reasonable distribution of reactive power between DGs by adjusting the virtual impedance value. To address the grid voltage drop caused by the introduction of virtual impedance and load changes, the secondary voltage control based on the consensus algorithm is used to restore the voltage level of the grid to ensure the stability of the grid. The proposed strategy does not require the line impedance value information, but needs the power information of the adjacent DG to adaptively adjust the virtual impedance. It achieves accurate reactive power distribution and voltage recovery even when some DG faults occur, enhancing the reliability of the system. Our simulation results demonstrate the feasibility and effectiveness of the proposed strategy. Related Articles | Metrics

Select

Dynamic evaluation of coordinated enhancement for pollution control and carbon reduction in urban road traffic 2024, 38 (1):  273-280.  Abstract ( 98 )   PDF (4017KB) ( 140 )   Save Guided by the goal of carbon peaking and carbon neutralization, urban traffic pollutants and CO2 emission reduction (hereinafter pollution control and carbon reduction) have become an urgent task. To this end, a system dynamic model with the consideration of the sunk cost effect and improvement of citizens’ awareness of green trips is built by introducing voluntary advocacy strategy. The principle of sunk cost effect is employed to clarify the inducing mechanism of new trips demand. Through dynamic simulation and comparative analysis of different scenarios, the synergetic strategy of pollution control and carbon reduction for small passenger cars is explored. Our results show the air pollution charging fee is a “double-edged sword” for pollution control and carbon reduction of small passenger cars. Moderate charging not only mitigates traffic congestion, but also reduces emission reduction. However, overcharging easily induces new demand for trips, causing some side effects. Compared with the baseline scenario, our proposed model decreases the PM pollution, CO2 emissions and greenhouse effect of small passenger cars by 33.98%, 21.72% and 30.69% respectively, demonstrating the model’s synergistic impacts on reducing pollution, carbon and inhibiting the growth of side effects. Related Articles | Metrics

Select

Research on optimal scheduling of microgrid using improved Northern Goshawk algorithm 2024, 38 (1):  281-289.  Abstract ( 136 )   PDF (1281KB) ( 107 )   Save The microgrid system normally consists of a variety of distributed power sources. To cut the operating cost of the microgrid, intelligent algorithms are often employed to dispatch the microgrid. Intelligent algorithms are prone to fall into local optimal solutions when solving microgrid scheduling models, resulting in poor accuracy. Therefore, based on the Northern Goshawk algorithm, this paper proposes a hybrid strategy improved Northern Goshawk algorithm (HNGO), which uses reverse learning, Metropolies criterion and adaptive T-distribution variation to enhance its accuracy. Meanwhile, a demand response model considering the output characteristics of renewable energy is built, so that the load curve is closer to the output curve of renewable energy. Then, a microgrid optimization scheduling model with the lowest daily operating cost is established, and HNGO is used to find the solution. Our simulation results show the proposed algorithm achieves accuracy, and our proposed demand response model significantly reduces fuel costs. Related Articles | Metrics

Select

Evolutionary game analysis of waste power battery recycling supervision from the perspective of prospect theory 2024, 38 (1):  290-297.  Abstract ( 94 )   PDF (2242KB) ( 93 )   Save Used power batteries have strong negative externalities, contrary to the original intention of new energy vehicle design. To promote the effective recycling of used power batteries, the prospect theory is coupled with evolutionary game theory, and the interests of the government, enterprises (automobile production) and the public are thoroughly considered so that the enterprises can be jointly supervised by the government and the public and a tripartite game model can be developed. Analogue numerical simulations are conducted for different scenarios of initial willingness, penalty composition, risk attitude coefficient and loss aversion coefficient, and in relation to awareness, reward and punishment mechanisms and profitability confidence of used power batteries in reality, analysis is made. Our study shows increasing the initial supervisory willingness of the public or the government promotes the recycling of used power batteries by enterprises; when the recycling strategy of enterprises is losing money, active recycling by enterprises is enhanced by increasing the amount of compensation from enterprises to the public, and decreasing the risk attitude coefficients and loss aversion coefficients of enterprises; in the recycling process of used power batteries, joint supervision is superior to individual supervision. Related Articles | Metrics

Select

Operation optimization of logistics primary centralized network under bi-level programming model 2024, 38 (1):  298-307.  Abstract ( 114 )   PDF (2939KB) ( 113 )   Save The high average cost and the low overall profit margin of China’s logistics industry are not conducive to the sustainable development of the industry and online consumer market. This paper proposes a primary centralized logistics operation based on freight consolidation to cut costs and improve efficiency in the logistics industry. It explores the efficient and low-cost operation mode of express transportation logistics, conforming to China’s actual conditions. First, this paper takes logistics and customer contact outlets as the starting point to build a bi-level programming model to cut costs and increase profits. Then, the game analysis is made on whether the logistics providers and users choose the strategy built by this model. Finally, the data of express outlets are empirically analyzed by seeking the the optimal solution of the strategy model through the peak searching algorithm. The time constraint in the implementation of the centralized strategy is further improved according to the solution of the shortest path problem. Our theoretical and empirical results show the centralization strategy of logistics outlets improves efficiency and reduces costs. The peak searching algorithm and strategy game effectively address the problems of the bi-level programming model in logistics optimization. Related Articles | Metrics

Select

Lithium-ion battery life prediction under driving conditions based on SCSSA-CNN-BiLSTM 2024, 38 (1):  308-318.  Abstract ( 171 )   PDF (3325KB) ( 436 )   Save  As lithium-ion batteries become increasingly popular, the battery life prediction is of crucial importance. Accurate prediction of the remaining useful life (RUL) of lithium-ion batteries is a critical part of their health management. In light of this, this paper proposes an algorithm SCSSA-CNN-BiLSTM, aming to perform RUL prediction for lithium-ion batteries used on electric vehicles. By combining convolutional neural networks (CNN), bidirectional long short-term memory (BiLSTM), and sine-cosine and cauchy mutation sparrow search algorithm (SCSSA), our algorithm forms a novel hybrid neural network that enhances the accuracy and stability of RUL predictions for lithium-ion batteries. CNN is employed for comprehensive extraction of deep features related to the state of health (SOH) of the batteries, while BiLSTM investigates these deep features bidirectionally and generates RUL predictions through dense layers. To validate the effectiveness of the proposed approach, battery data from NASA are compared with multiple commonly used models. Our research results show the hybrid model improves the coefficient of determination (R2) by 4%～23% and reduces the RUL absolute error to 1, demonstrating a higher prediction accuracy. The cyclic experiments are conducted later on vehicles under CLTC dynamic conditions, and predictions are made on battery life degradation. Our results reveal the SCSSA-CNN-BiLSTM model yields a root mean square error (RMSE) of 1.64 A·h and an R2 value of 0.98, delivering strong predictive and generalization performances. Related Articles | Metrics

Select

Performance degradation prediction of PEMFC under dynamic operating conditions based on WOA-BiGRU 2024, 38 (1):  319-327.  Abstract ( 108 )   PDF (2691KB) ( 74 )   Save Proton exchange membrane fuel cell (PEMFC) is an important modern sustainable energy power generation device, and accurate estimation of its performance degradation is crucial for practical applications. Conventional data-driven approaches lack consideration of aging mechanisms, leading to unsatisfying handling of voltage recovery during performance degradation. By analyzing various characteristic information in PEMFC operational data, this paper proposes a dynamic operational condition-based prediction method for PEMFC performance degradation. First, the random forest algorithm is employed for data feature analysis to determine the features used for model training. Subsequently, a bidirectional gated recurrent units (BiGRU) model is built, and parameter optimization is performed using the whale optimization algorithm (WOA). Finally, the optimized BiGRU model is utilized for predicting PEMFC performance degradation, and the prediction effectiveness is evaluated. Experimental results on the PEMFC dynamic data set show the prediction accuracy is improved by 28.1%～33.7% compared with that of GRU and increased by 25.5%～31.2% compared with that of BiGRU. Related Articles | Metrics

"Intelligent robot perception, Planning and Application Technology" special column

Select

Improved UAV path planning study for JPS 2024, 38 (1):  328-337.  Abstract ( 148 )   PDF (3871KB) ( 114 )   Save Although the traditional JPS algorithm reduces the number of expansion nodes during path planning, it needs to find a jump point for each node it generates, which thus increases the number of expansion nodes in the obstacle area, resulting in the time cost of generating nodes and the path cost. And the cost of visiting nodes is higher. To address this problem, this paper proposes an S-JPS algorithm that improves the jump search rules. On the heuristic function: This algorithm introduces distance and direction information. The specific operation is: First multiply the distance between the starting point and the end point by the weight representing the distance information, then multiply the cosine value of the direction of the starting point and the end point by the weight representing the direction information, and finally linearly combine the above two steps. The cost of generating a large number of nodes is reduced. The JPS algorithm uses Manhattan distance or Euclidean distance to estimate the distance from the node to the target node to evaluate the priority of the node and determine the search direction. In contrast, the S-JPS algorithm more accurately describes the distance from the current point to the target. The estimated cost of the point, thereby reduces the time cost, path cost and number of visited nodes. Regarding the node update rules: In order to overcome the difficulty of back-end trajectory optimization, the inflection points have been trimmed to further improve the smoothness of the path. The specific operations are: For all extended nodes (a0, a1,…, aN), if the slopes of the straight lines an-1an and anan+1 formed by adjacent nodes are different, connect nodes an-1 and an+1. If the straight line an-1an+1 does not pass through the obstacle, discard the original an-1an and anan+1, and retain the line segment an-1an+1. The new path obtained by analogy is the path obtained under the node update rule.For the problem that the path planned in the back-end trajectory optimization is not smooth, a trajectory optimization method based on a mixture of Bezier curves and straight lines is proposed to smooth the generated trajectory to make its curvature more continuous and the generated trajectory smoother. This algorithm requires the curvature of the Bezier curve to be continuous with the straight line segment, so the curvature at the connection between the Bezier curve and the straight line segment is 0. Among them, the most important part of using Bezier curve to replace the original straight line segment is the selection of control points, and the selection method of control points is the formula (13) in the text. Through simulation experiment analysis and compared with the JPS algorithm, our results show S-JPS algorithm reduces a large number of visited nodes in the path planning under the same map, and improves the speed of path planning. Finally, the S-JPS algorithm is applied to an dependently built UAV for experiments. Under the same planning task with the same starting point, end point and actual physical environment, the S-JPS algorithm reduceds the path planning time by 98.6% compared to the JPS algorithm. The cost is down by 81.1% and the number of visited nodes by 99.7%, meeting the high demand for real-time path planning of UAVs. Related Articles | Metrics

Select

Path planning of picking manipulator with improved RRT 2024, 38 (1):  338-345.  Abstract ( 115 )   PDF (1872KB) ( 98 )   Save To address the problems that the picking robot arm employing the traditional fast random extended tree (RRT) algorithm requires a long time to search the path in the orchard working environment and the final path is not smooth with many inflection points, this paper proposes an improved RRT obstacle avoidance algorithm adopting Gaussian sampling strategy, which reduces the randomness of sampling, avoids generating more unnecessary random trees, and increases the orientation of programming. Then, A* cost function is added to remove redundant points of the path. Finally, greedy algorithm is used to simplify the path and reduce its inflection points, so that the robot arm can move along the optimal path quickly and locate the target point accurately. Our simulation results show the improved algorithm effectively reduces the time of path planning and cuts the path lengths, demonstrating its fairly good effectiveness and practicality. Related Articles | Metrics

Select

Research on global cone bucket mapping algorithm for FSAC field environment 2024, 38 (1):  346-354.  Abstract ( 84 )   PDF (2766KB) ( 142 )   Save To remedy the failures of path planning due to the limited identification of cones and barrels in the “U-bend” condition in FSAC racing car’s high-speed tracking, this paper proposes a cone and barrel map construction algorithm based on lidar and integrated inertial navigation system. The algorithm extracts the cone barrel center point cloud from the laser point cloud of the current frame, and projects the cone barrel point cloud in the laser coordinate system to the map coordinate system by multiplying the calibration matrix from radar to integrated inertial navigation system and the pose matrix of the vehicle in the map coordinate system calculated in real time by the integrated inertial navigation system, completing the construction and updating the cone barrel map. The algorithm is verified on vehicles and the results of three experiments show its average recall rate reads 98.7% and its average accuracy stands at 98.1%. The constructed map provides the planning algorithm to fit the global optimal path of the track for accelerated tracking, improving the perception and prediction ability of the car and the efficiency of path planning. Related Articles | Metrics

Select

Robot path planning research with improved marine predator algorithm 2024, 38 (1):  355-367.  Abstract ( 120 )   PDF (2986KB) ( 117 )   Save This paper proposes a multi-strategy Improved Marine Predator Algorithm (IMPA) to address the Marine Predator Algorithm’s (MPA) problems of slow convergence, low convergence accuracy, and tendency to fall into local optimum. The proposed algorithm introduces a logistic chaotic mapping to initialize the population and increase the diversity of the predator population; an adaptive moving step dynamic adjustment strategy based on the current iteration number t enhances the ability of the algorithm to escape from local optimum; a mid-pipeline algorithm (MA) is added in the late iteration of IMPA, and a free particle position update method based on the mid-pipeline strategy accelerates the position update of the predator and enhances the algorithm’s accuracy and optimization search speed, avoiding falling into local optimum. Finally, the search process is further balanced and the global and local adaptability is enhanced by changing the IMPA stage to transform the search process. Six benchmark test functions are selected to test the performance of the algorithm. Our test results show IMPA converges faster and achieves a higher convergence accuracy. Finally, the improved algorithm is applied in mobile robot path planning, and the simulation results show the algorithm plans a shorter path and achieves a higher search efficiency. Related Articles | Metrics

Select

Spatial trajectory planning method for joints of six-axis robotic arm based on improved particle swarm algorithm 2024, 38 (1):  368-378.  Abstract ( 168 )   PDF (4598KB) ( 252 )   Save This paper takes the xArm6 robotic arm as the research object and proposes a joint space trajectory planning method based on the time-optimal 3-5-3 segmented polynomial interpolation of the improved particle swarm algorithm. The proposed method improves the operation efficiency and stability of the six-axis robotic arm. It takes the optimal running time of the robotic arm as the objective, and under the constraints of speed, acceleration and variable acceleration, the interpolation time of each segment is optimized by the improved particle swarm algorithm which introduces adaptive inertia weights and probabilistic jump characteristics. Compared with the traditional particle swarm algorithm, the improved particle swarm algorithm reaches a faster iteration speed and is less likely to fall into local optimum. Our results of robotic arm motion simulation show the robotic arm operates smoothly, and the six joints experience not abrupt, but continuous changes in positions, velocities and acceleration, demonstrating the practicality and effectiveness of the method. Related Articles | Metrics