{"title":"考虑驾驶员意愿的再生制动力分配策略研究","authors":"Shunming Li, Yuqing Su, Cong Shen, Yun Bai","doi":"10.26480/jmerd.05.2019.172.176","DOIUrl":null,"url":null,"abstract":"The regenerative braking energy recovery system of electric vehicle can effectively improve its mileage. In this paper, we took the front-drive EV as the object to analyze the braking force allocation during its braking process. After considering ECE regulation, the motor peak torque and battery charging power as the main restrictive conditions and combining them with driver braking intensity discrimination characteristics, a new control strategy of regenerative braking force allocation was proposed for the vehicle. Then, simulation model was established on the MATLAB/Simulink software platform. At the same time, the initial velocity is 30km/h, 60km/h and 100km/h respectively, and the braking intensity is 0.1 and 0.5 respectively, which were set as simulation conditions. The simulation results of the strategy were compared to that of ideal braking force allocation strategy under the middle braking intensity condition. The results show that this control strategy can effectively achieve the braking energy recovery, and the efficiency at each initial braking speed of low, medium and high speeds is higher than that of ideal braking force allocation strategy.","PeriodicalId":16153,"journal":{"name":"Journal of Mechanical Engineering Research and Developments","volume":"186 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"STUDY ON THE ALLOCATION STRATEGY OF REGENERATIVE BRAKING FORCE WITH A DRIVER’S INTENTION\",\"authors\":\"Shunming Li, Yuqing Su, Cong Shen, Yun Bai\",\"doi\":\"10.26480/jmerd.05.2019.172.176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The regenerative braking energy recovery system of electric vehicle can effectively improve its mileage. In this paper, we took the front-drive EV as the object to analyze the braking force allocation during its braking process. After considering ECE regulation, the motor peak torque and battery charging power as the main restrictive conditions and combining them with driver braking intensity discrimination characteristics, a new control strategy of regenerative braking force allocation was proposed for the vehicle. Then, simulation model was established on the MATLAB/Simulink software platform. At the same time, the initial velocity is 30km/h, 60km/h and 100km/h respectively, and the braking intensity is 0.1 and 0.5 respectively, which were set as simulation conditions. The simulation results of the strategy were compared to that of ideal braking force allocation strategy under the middle braking intensity condition. The results show that this control strategy can effectively achieve the braking energy recovery, and the efficiency at each initial braking speed of low, medium and high speeds is higher than that of ideal braking force allocation strategy.\",\"PeriodicalId\":16153,\"journal\":{\"name\":\"Journal of Mechanical Engineering Research and Developments\",\"volume\":\"186 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mechanical Engineering Research and Developments\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.26480/jmerd.05.2019.172.176\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mechanical Engineering Research and Developments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26480/jmerd.05.2019.172.176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
STUDY ON THE ALLOCATION STRATEGY OF REGENERATIVE BRAKING FORCE WITH A DRIVER’S INTENTION
The regenerative braking energy recovery system of electric vehicle can effectively improve its mileage. In this paper, we took the front-drive EV as the object to analyze the braking force allocation during its braking process. After considering ECE regulation, the motor peak torque and battery charging power as the main restrictive conditions and combining them with driver braking intensity discrimination characteristics, a new control strategy of regenerative braking force allocation was proposed for the vehicle. Then, simulation model was established on the MATLAB/Simulink software platform. At the same time, the initial velocity is 30km/h, 60km/h and 100km/h respectively, and the braking intensity is 0.1 and 0.5 respectively, which were set as simulation conditions. The simulation results of the strategy were compared to that of ideal braking force allocation strategy under the middle braking intensity condition. The results show that this control strategy can effectively achieve the braking energy recovery, and the efficiency at each initial braking speed of low, medium and high speeds is higher than that of ideal braking force allocation strategy.
期刊介绍：
The scopes of the journal include, but are not limited to, the following topics: • Thermal Engineering and Fluids Engineering • Mechanics • Kinematics, Dynamics, & Control of Mechanical Systems • Mechatronics, Robotics and Automation • Design, Manufacturing, & Product Development • Human and Machine Haptics Specific topics of interest include: Advanced Manufacturing Technology, Analysis and Decision of Industry & Manufacturing System, Applied Mechanics, Biomechanics, CAD/CAM Integration Technology, Complex Curve Design, Manufacturing & Application, Computational Mechanics, Computer-aided Geometric Design & Simulation, Fluid Dynamics, Fluid Mechanics, General mechanics, Geomechanics, Industrial Application of CAD, Machinery and Machine Design, Machine Vision and Learning, Material Science and Processing, Mechanical Power Engineering, Mechatronics and Robotics, Artificial Intelligence, PC Guided Design and Manufacture, Precision Manufacturing & Measurement, Precision Mechanics, Production Technology, Quality & Reliability Engineering, Renewable Energy Technologies, Science and Engineering Computing, Solid Mechanics, Structural Dynamics, System Dynamics and Simulation, Systems Science and Systems Engineering, Vehicle Dynamic Performance Simulation, Virtual-tech Based System & Process-simulation, etc.
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