Battery aging-minimal speed control of autonomous heavy-duty electric trucks in adaptation to highway topography and traffic  被引量:3

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作  者:ZHANG YongZhi WANG Chun YU QuanQing ZHENG Ling 

机构地区:[1]College of Mechanical and Vehicle Engineering,Chongqing University,Chongqing 400044,China [2]School of Mechanical Engineering,Sichuan University of Science and Engineering,Zigong 643000,China [3]School of Automotive Engineering,Harbin Institute of Technology,Weihai 264209,China

出  处:《Science China(Technological Sciences)》2023年第10期2942-2957,共16页中国科学(技术科学英文版)

基  金:funded by the Research Start-Up Funding of Chongqing University(Grant No.02090011044160);the National Natural Science Foundation of China(Grant No.51907136)。

摘  要:The development of battery electric(BE)heavy-duty trucks(HDTs)is highly limited to the short cycling life of batteries.In this paper,we propose a battery aging-conscious control strategy for extended battery life by optimizing the speed trajectory of BE HDT.A state-space model is constructed by connecting the vehicle dynamics and battery state of charge,and a mechanism-based aging model of battery is then introduced to formulate the optimization problem for minimal battery aging and energy consumption.The optimization problem is solved within a model predictive control framework for the real-time speed control of the vehicle.A non-cooperative platooning controller is further developed for the vehicle in adaptation to the traffic,where the intervehicular distance is controlled for reducing the air drag coefficient so that both the energy consumption and battery aging are improved.Simulation results show that for the single-vehicle controller,the battery degradation and energy consumption are,respectively,reduced by up to 25.7%and 3.2%compared with the cruise control strategy.Based on the non-cooperative controller,the HDT is able to follow preceding vehicles with different parameters with battery aging and energy consumption further,respectively,reduced by 2%–5%and 9%–10%compared with those of the single-vehicle controller.

关 键 词:electric trucks speed trajectory planning battery aging model predictive control non-cooperative platooning 

分 类 号:U469.72[机械工程—车辆工程]

 

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