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2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)最新文献

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MRAC-based identification method of iron loss resistance for permanent magnet synchronous motor* 基于mrac的永磁同步电机铁损电阻识别方法*
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338611
Xiaohua Zeng, Hongxu Chen, D. Song, Chen Cui
{"title":"MRAC-based identification method of iron loss resistance for permanent magnet synchronous motor*","authors":"Xiaohua Zeng, Hongxu Chen, D. Song, Chen Cui","doi":"10.1109/CVCI51460.2020.9338611","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338611","url":null,"abstract":"In order to calculate the iron loss resistance of the permanent magnet synchronous motor (PMSM) in real time, this paper presents an identification method of iron loss resistance based on model reference adaptive control (MRAC), and designs the adaptive mechansim by Popov's hyperstability theory. According to the equivalent phase d-q circuit model of PMSM considering the iron loss resistance, the simplified PMSM model in the original Simulink motor library is modified. The MRAC-based identification method is simulated on the modified PMSM system under steady and dynamic conditions. The simulation results show that the estimated value of iron loss resistance can effectively converge to the real value. By adjusting the PI parameters and adding a low-pass filter, the robustness and dynamic characteristics of the identification system are improved.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116870010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Summarization of Sensorless Positioning and Speed Measurement for Permanent Magnet Synchronous Motor 永磁同步电机无传感器定位与速度测量技术综述
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338526
Yuxin Jin, Zhen Jia, Qiang Chen, Peichang Yu, Jie Li
{"title":"Summarization of Sensorless Positioning and Speed Measurement for Permanent Magnet Synchronous Motor","authors":"Yuxin Jin, Zhen Jia, Qiang Chen, Peichang Yu, Jie Li","doi":"10.1109/CVCI51460.2020.9338526","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338526","url":null,"abstract":"The precise and efficient control of permanent magnet synchronous motor (PMSM) relies on real-time and accurate position and speed information. The traditional motor position detection needs to be realized by position sensor. However, for PMSM used in maglev transportation, the sensor scheme is complex and high cost. Therefore, the paper takes position and speed sensorless detection of PMSM as the research goal, and systematically summarizes the principles, applicable environment and improved methods from zero-low speed and medium-high speed, which provides reference for sensorless control of PMSM for rail transit.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129926457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on Predictive Cruise Control of Electric Vehicle Based on Time-Varying Model Prediction 基于时变模型预测的电动汽车预测巡航控制研究
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338569
Dongmei Wu, Huanfeng Liu, F. Zhao, Y. Li
{"title":"Research on Predictive Cruise Control of Electric Vehicle Based on Time-Varying Model Prediction","authors":"Dongmei Wu, Huanfeng Liu, F. Zhao, Y. Li","doi":"10.1109/CVCI51460.2020.9338569","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338569","url":null,"abstract":"For the problem of ecological cruise control integrating the terrain information of the road ahead, in order to input the actual slope changed with time over the prediction horizon, a linear time-varying model predictive controller is designed in this paper based on the traditional theory of model predictive control. The analysis of vehicle driving on flat road and hilly road is simulated by MATLAB/Simulink, results show that it has a good effect on energy saving at the cost of shorter distance. In addition, the energy consumption under different control targets and the influence of weight coefficients on vehicle economy under the same target are also analyzed and compared.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130092295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Research on Failure Mechanism for Distributed Drive Vehicle Based on Co-simulation of Carsim and Matlab 基于Carsim和Matlab联合仿真的分布式驱动车辆失效机理研究
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338637
Ling Gang, Ge Pingshu, Z. Jiaqi, Zhang Tao, Zhao Kailan, L. Junjie
{"title":"Research on Failure Mechanism for Distributed Drive Vehicle Based on Co-simulation of Carsim and Matlab","authors":"Ling Gang, Ge Pingshu, Z. Jiaqi, Zhang Tao, Zhao Kailan, L. Junjie","doi":"10.1109/CVCI51460.2020.9338637","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338637","url":null,"abstract":"Distributed drive vehicles adopt multi-motor distributed drive, which makes it show advantages that traditional vehicles do not have, at the same time, it results in new problems to the reliability of the system. This paper takes four-wheel independent driven vehicle as the research object. Aiming at the failure of the in-wheel motors of distributed drive vehicles,a distributed motor drive vehicle model is built based on Carsim and Simulink. Based on the simulation verification of the established model, the simulation experiments for failure conditions are designed, and the results are analyzed. The results show that the established model basically satisfies the experimental requirements, and the failure analysis can provide a basis for subsequent fault-tolerant controller design.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123482755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Real-time Model Predictive Controller for Vehicle Lateral Stabilization under Extreme Conditions 极端条件下车辆横向稳定的实时模型预测控制器
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338640
Meng Gao, Ping Wang, Zihan Li, Hanghang Liu, Fei Wang
{"title":"Real-time Model Predictive Controller for Vehicle Lateral Stabilization under Extreme Conditions","authors":"Meng Gao, Ping Wang, Zihan Li, Hanghang Liu, Fei Wang","doi":"10.1109/CVCI51460.2020.9338640","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338640","url":null,"abstract":"Under extreme driving conditions, the tire lateral force is easily saturated, which should be considered for better performance in vehicle stability control, as well as the safety constraints and real-time response. To address the above problem, a real-time model predictive controller for four wheel independent motor-drive electric vehicles is proposed to improve the lateral stability. First, considering the saturation characteristic of the tire dynamics on a slippery road, the tire model is developed into the piecewise form of linear and saturation regions, which extracts the main nonlinearity of tire. Second, the additional yaw moment is determined to achieve the control objectives of lateral stability and handling performance. Then, the additional yaw moment is distributed into torques acting on each motor by optimizing the tire load rates. Finally, co-simulations with MATLAB/CarSim and hardware-in-the-loop simulation are performed, and the fast solution of optimization problem is realized based on C-language. The results show that lateral stability and handling performance are efficiently improved, and the real-time performance can be ensured with a sampling time as 5ms.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126289077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PI Observer for Sensorless Field Oriented Control of Permanent Magnet Synchronous Motor 永磁同步电机无传感器磁场定向控制的PI观测器
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338483
Yujiang Wei, Qin Shi, Jianxin Zheng, Mingwei Wang, Lin He
{"title":"PI Observer for Sensorless Field Oriented Control of Permanent Magnet Synchronous Motor","authors":"Yujiang Wei, Qin Shi, Jianxin Zheng, Mingwei Wang, Lin He","doi":"10.1109/CVCI51460.2020.9338483","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338483","url":null,"abstract":"The angular velocity and rotor position of the motor are computed by PI observer. Clark and Park transformations is utilized to establish a dynamics model of the motor. Space vector pulse width modulation algorithm is used for voltage modulation. The main control chip of the hardware board selects TI's TMS320F28035, and the power device selects Mitsubishi's IPM(PS22A79). The hardware board is designed to test and verify the PI observer. The test results are analyzed and indicated that the PI observer is a good candidate for sensorless field oriented control of permanent magnet synchronous motor.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122544434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Research on Accurate Adjustment of Braking Force and Vehicle Yaw Stability Control Strategy Based on New Electro-hydraulic Brake System 基于新型电液制动系统的制动力精确调节及车辆偏航稳定性控制策略研究
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338551
M. Wang, Xuanyao Wang, Yongyan Xie
{"title":"Research on Accurate Adjustment of Braking Force and Vehicle Yaw Stability Control Strategy Based on New Electro-hydraulic Brake System","authors":"M. Wang, Xuanyao Wang, Yongyan Xie","doi":"10.1109/CVCI51460.2020.9338551","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338551","url":null,"abstract":"A new electro-hydraulic brake system with the structural characteristics of dual master cylinders is presented in this paper and considering the disadvantage of functional backup of the conventional vehicle stability control system, three vehicle yaw stability control strategy are presented. Firstly, the three-closed-loop pressure following PI control algorithm of the new electro-hydraulic brake system is studied to make it quickly follow the target pressure value; Secondly, based on analyzing the two-degree-of-freedom(2-DOF) vehicle dynamic model, the upper-layer, lower-layer controller were designed respectively using the hierarchical control strategy. The upper-layer controller adopted PID, Fuzzy and PID + Fuzzy three controls for the front wheel, rear wheel and front wheel + rear wheel of the vehicle respectively to calculate the additional yaw moment; Then the additional yaw moment is distributed to the single action wheel by lower-layer controller, and then motor control command is calculated by the target braking torque value to ensure that the additional yaw moment generated by the brake actuator tracks the desired yaw moment value of the upper-layer controller in real time. Finally, in order to verify the feasibility of the control strategy and the effectiveness of the algorithm, a co-simulation experiment of CarSim and MATLAB/Simulink is established. The results show that the control algorithm can match the characteristics of the electro-hydraulic brake system and has a good failure backup function and yaw stability control efficiency.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122692889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Novel Starlight-RGB Colorization Method Based on Image Pair Generation for Autonomous Driving 基于图像对生成的自动驾驶星光- rgb着色新方法
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338603
Ziqing Cheng, Jian Li, Xiaohui Yang, Zhenping Sun
{"title":"A Novel Starlight-RGB Colorization Method Based on Image Pair Generation for Autonomous Driving","authors":"Ziqing Cheng, Jian Li, Xiaohui Yang, Zhenping Sun","doi":"10.1109/CVCI51460.2020.9338603","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338603","url":null,"abstract":"It is a difficult challenge for humans to carry out environmental perception work at night and in low-light scenes. Depending on its extraordinary working performance in the dark, starlight camera is widely used in night driving assistance and various surveillance missions. However, the starlight camera images are lack of colorful information, which prevents users from understanding. This paper proposes a novel approach for colorizing starlight images using Generative Adversarial Network (GAN) architecture. The proposed method overcomes the time-space asynchronism of traditional heterogeneous data acquisition. We firstly introduce starlight-RGB image pairs generation. Inspired by 3D perspective transformation, we use LiDAR, camera and Inertial Measurement Unit(IMU) data to create generated visible images. We collect synchronous visible iamges, LiDAR points data and IMU data in the daytime and acquire LiDAR, starcam and IMU data at night. Such image pair generation method overcomes the difficulty of obtaining pairs of data and image pairs are aligned at pixel-level. As there are no reflection LiDAR points in the sky, the perspective projection images have no content in the sky areas. Based on supervised image-to-image translation GAN architecture, we use daytime RGB images as unpaired data, which is in order to restore the texture and color of the sky. We use KITTI dataset as validation, and get good experimental performance on our datasets.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128112699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Longitudinal Tracking Control of Vehicle Platooning Using DDPG-based PID 基于ddpg的车辆队列纵向跟踪控制
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338516
Junru Yang, Xingliang Liu, Shidong Liu, Duanfeng Chu, Liping Lu, Chaozhong Wu
{"title":"Longitudinal Tracking Control of Vehicle Platooning Using DDPG-based PID","authors":"Junru Yang, Xingliang Liu, Shidong Liu, Duanfeng Chu, Liping Lu, Chaozhong Wu","doi":"10.1109/CVCI51460.2020.9338516","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338516","url":null,"abstract":"Cooperative adaptive cruise control (CACC) has important significance for the development of the connected and automated vehicle (CAV) industry. In this paper, a learning control method combined Deep Deterministic Policy Gradient and Proportional-Integral-Derivative (DDPG-PID) controller is proposed. The main contribution of this study is automating the PID weight tuning process by formulating this objective as a deep reinforcement learning (DRL) problem. Based on the Hardware-in-the-Loop (HIL) simulation platform, the DDPG-PID controller is compared with the conventional PID controller under the test condition. Experiment results indicate that on 38.95% stability time in vehicular platooning system is decreased by utilizing the proposed method. The performance of maximum distance error is also improved efficiently, which is reduced by 60.94%. The research in this paper is a further development of learning control method and provides a new idea for the practical application of DRL algorithm in industrial field.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115459239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Collaborative Control with Nonlinear Observer for the Stability of Electric Vehicles 基于非线性观测器的电动车稳定性协同控制
2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI) Pub Date : 2020-12-18 DOI: 10.1109/CVCI51460.2020.9338442
Yan Ma, Jian Chen, Junmin Wang, D. Narang
{"title":"Collaborative Control with Nonlinear Observer for the Stability of Electric Vehicles","authors":"Yan Ma, Jian Chen, Junmin Wang, D. Narang","doi":"10.1109/CVCI51460.2020.9338442","DOIUrl":"https://doi.org/10.1109/CVCI51460.2020.9338442","url":null,"abstract":"This paper designs a novel collaborative control approach, including the longitudinal and lateral motion control, to guarantee the vehicle stability by the estimated vehicle states of electric vehicles. A nonlinear observer is developed to observe the lateral velocity and tire-road friction coefficient by a Dugoff's tire model. Moreover, a Lyapunov-based method is utilized to prove that the estimated errors converge to zero. The collaborative control is converted into a tracking problem by establishing a reference model. According to the estimated vehicle states and reference model, a passivity-based control strategy based on the port-Hamiltonian model is adopted to follow the referenced vehicle states and ensure the stable planar motions, and the asymptotic stability of the proposed controller is proved. In addition, a wheel torque distribution considering the transfer of vertical loads is designed to maximize the utilization of tire adhesive forces. Finally, simulation cases demonstrate the effectiveness of the designed nonlinear observer and controller.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124857713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
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