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| Real-time energy management strategy based on predictive cruise control for hybrid electric vehicles |
| XiongxiongYou1,2,XiaohongJiao1,2,ZeyiWei3,YahuiZhang3 |
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| (1 Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Yanshan University, Qinhuangdao 066000, Hebei, China
2 School of Electrical Engineering, Yanshan University, Qinhuangdao 066000, Hebei, China;3 School of Mechanical Engineering, Yanshan University, Qinhuangdao 066000, Hebei, China) |
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| 摘要: |
| With the help of traffic information of the connected environment, an energy management strategy (EMS) is proposed based
on preceding vehicle speed prediction, host vehicle speed planning, and dynamic programming (DP) with PI correction to
improve the fuel economy of connected hybrid electric vehicles (HEVs). A conditional linear Gaussian (CLG) model for
estimating the future speed of the preceding vehicle is established and trained by utilizing historical data. Based on the
predicted information of the preceding vehicle and traffic light status, the speed curve of the host vehicle can ensure that the
vehicle follows safety and complies with traffic rules simultaneously as planned. The real-time power allocation is composed
of offline optimization results of DP and the real-time PI correction items according to the actual operation of the engine.
The effectiveness of the control strategy is verified by the simulation system of HEVs in the interconnected environment
established by E-COSM 2021 on the MATLAB/Simulink and CarMaker platforms. |
| 关键词: Connected HEVs · EMS · Gaussian model prediction · Speed planning · DP |
| DOI：https://doi.org/10.1007/s11768-022-00096-w |
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| 基金项目:This work was supported by the National Natural Science Foundation of China (No. 61973265), the Natural Science Foundation of Hebei Province (No. E2021203079) and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, Hebei Province (No. C20210323). |
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| Real-time energy management strategy based on predictive cruise control for hybrid electric vehicles |
| Xiongxiong You1,2,Xiaohong Jiao1,2,Zeyi Wei3,Yahui Zhang3 |
| (1 Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Yanshan University, Qinhuangdao 066000, Hebei, China
2 School of Electrical Engineering, Yanshan University, Qinhuangdao 066000, Hebei, China;3 School of Mechanical Engineering, Yanshan University, Qinhuangdao 066000, Hebei, China) |
| Abstract: |
| With the help of traffic information of the connected environment, an energy management strategy (EMS) is proposed based
on preceding vehicle speed prediction, host vehicle speed planning, and dynamic programming (DP) with PI correction to
improve the fuel economy of connected hybrid electric vehicles (HEVs). A conditional linear Gaussian (CLG) model for
estimating the future speed of the preceding vehicle is established and trained by utilizing historical data. Based on the
predicted information of the preceding vehicle and traffic light status, the speed curve of the host vehicle can ensure that the
vehicle follows safety and complies with traffic rules simultaneously as planned. The real-time power allocation is composed
of offline optimization results of DP and the real-time PI correction items according to the actual operation of the engine.
The effectiveness of the control strategy is verified by the simulation system of HEVs in the interconnected environment
established by E-COSM 2021 on the MATLAB/Simulink and CarMaker platforms. |
| Key words: Connected HEVs · EMS · Gaussian model prediction · Speed planning · DP |
