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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Main Authors: Sheng Zhang, Xiangtao Zhuan
Format: Article
Language:English
Published: Hindawi Limited 2019-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2019/7971594
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spelling 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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