Study on Adaptive Cruise Control Strategy for Battery Electric Vehicle
This paper studies the control strategy for adaptive cruise control (ACC) system on a battery electric vehicle (BEV) in the car-following process, and the highlight of this paper is that the regeneration braking of BEV is considered in the car-following process. The hierarchical control structure is...
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2019-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/7971594 |
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doaj-7e7a3e4ffc264e5688b32e4376ab82152020-11-25T02:21:17ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472019-01-01201910.1155/2019/79715947971594Study on Adaptive Cruise Control Strategy for Battery Electric VehicleSheng Zhang0Xiangtao Zhuan1School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, ChinaSchool of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, ChinaThis paper studies the control strategy for adaptive cruise control (ACC) system on a battery electric vehicle (BEV) in the car-following process, and the highlight of this paper is that the regeneration braking of BEV is considered in the car-following process. The hierarchical control structure is adopted for the ACC system. And the structure contains an upper controller and a lower controller. In the upper controller, multiple objectives including the safety, tracking, comfort, and energy consumption are optimized by using the model predictive control (MPC) method. In the lower controller, the energy is recovered during braking. So the energy economy is improved by reducing energy consumption and increasing energy recovery. The proposed ACC strategy is evaluated in simulation experiment. In the simulation experiment, safe tracking for the front vehicle is guaranteed, and the comfort and the energy economy are improved greatly. So the proposed adaptive cruise control strategy can make ACC more widely used in BEVs.http://dx.doi.org/10.1155/2019/7971594 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sheng Zhang Xiangtao Zhuan |
spellingShingle |
Sheng Zhang Xiangtao Zhuan Study on Adaptive Cruise Control Strategy for Battery Electric Vehicle Mathematical Problems in Engineering |
author_facet |
Sheng Zhang Xiangtao Zhuan |
author_sort |
Sheng Zhang |
title |
Study on Adaptive Cruise Control Strategy for Battery Electric Vehicle |
title_short |
Study on Adaptive Cruise Control Strategy for Battery Electric Vehicle |
title_full |
Study on Adaptive Cruise Control Strategy for Battery Electric Vehicle |
title_fullStr |
Study on Adaptive Cruise Control Strategy for Battery Electric Vehicle |
title_full_unstemmed |
Study on Adaptive Cruise Control Strategy for Battery Electric Vehicle |
title_sort |
study on adaptive cruise control strategy for battery electric vehicle |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2019-01-01 |
description |
This paper studies the control strategy for adaptive cruise control (ACC) system on a battery electric vehicle (BEV) in the car-following process, and the highlight of this paper is that the regeneration braking of BEV is considered in the car-following process. The hierarchical control structure is adopted for the ACC system. And the structure contains an upper controller and a lower controller. In the upper controller, multiple objectives including the safety, tracking, comfort, and energy consumption are optimized by using the model predictive control (MPC) method. In the lower controller, the energy is recovered during braking. So the energy economy is improved by reducing energy consumption and increasing energy recovery. The proposed ACC strategy is evaluated in simulation experiment. In the simulation experiment, safe tracking for the front vehicle is guaranteed, and the comfort and the energy economy are improved greatly. So the proposed adaptive cruise control strategy can make ACC more widely used in BEVs. |
url |
http://dx.doi.org/10.1155/2019/7971594 |
work_keys_str_mv |
AT shengzhang studyonadaptivecruisecontrolstrategyforbatteryelectricvehicle AT xiangtaozhuan studyonadaptivecruisecontrolstrategyforbatteryelectricvehicle |
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1724867255218470912 |