Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control

Shumin Ruan; Yue Ma; Qi Yan

doi:10.1007/978-981-16-6324-6_87

Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control

Shumin Ruan, Yue Ma^*, Qi Yan

^*Corresponding author for this work

School of Mechanical Engineering

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In order to take into account the tracking control effect and real-time performance of vehicle adaptive cruise control (ACC), a multi-objective control method based on explicit model predictive control (EMPC) is proposed; First, the model of adaptive cruise control is established. According to the predictive control theory, the multi-objective function and constraints of vehicle’s safety, tracking, economy and comfort are determined. Based on the multi parameter programming theory, the closed-loop model predictive control system based on repeated online optimization calculation is transformed into an equivalent explicit polyhedral piecewise affine (PWA) system. The optimal control law between the desired acceleration and the state variables is obtained by off-line calculation. Then the adaptive cruise control is realized by locating the current state zone and applying the explicit control law of the zone. The longitudinal tracking simulation results show that the designed control strategy has good tracking effect.

Original language	English
Title of host publication	Proceedings of 2021 Chinese Intelligent Systems Conference - Volume II
Editors	Yingmin Jia, Weicun Zhang, Yongling Fu, Zhiyuan Yu, Song Zheng
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	860-869
Number of pages	10
ISBN (Print)	9789811663239
DOIs	https://doi.org/10.1007/978-981-16-6324-6_87
Publication status	Published - 2022
Event	17th Chinese Intelligent Systems Conference, CISC 2021 - Fuzhou, China Duration: 16 Oct 2021 → 17 Oct 2021

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	804 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	17th Chinese Intelligent Systems Conference, CISC 2021
Country/Territory	China
City	Fuzhou
Period	16/10/21 → 17/10/21

Keywords

Adaptive cruise control
Explicit model predictive control
Intelligent electric vehicle

Access to Document

10.1007/978-981-16-6324-6_87

Cite this

Ruan, S., Ma, Y., & Yan, Q. (2022). Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control. In Y. Jia, W. Zhang, Y. Fu, Z. Yu, & S. Zheng (Eds.), Proceedings of 2021 Chinese Intelligent Systems Conference - Volume II (pp. 860-869). (Lecture Notes in Electrical Engineering; Vol. 804 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-6324-6_87

Ruan, Shumin ; Ma, Yue ; Yan, Qi. / Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control. Proceedings of 2021 Chinese Intelligent Systems Conference - Volume II. editor / Yingmin Jia ; Weicun Zhang ; Yongling Fu ; Zhiyuan Yu ; Song Zheng. Springer Science and Business Media Deutschland GmbH, 2022. pp. 860-869 (Lecture Notes in Electrical Engineering).

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title = "Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control",

abstract = "In order to take into account the tracking control effect and real-time performance of vehicle adaptive cruise control (ACC), a multi-objective control method based on explicit model predictive control (EMPC) is proposed; First, the model of adaptive cruise control is established. According to the predictive control theory, the multi-objective function and constraints of vehicle{\textquoteright}s safety, tracking, economy and comfort are determined. Based on the multi parameter programming theory, the closed-loop model predictive control system based on repeated online optimization calculation is transformed into an equivalent explicit polyhedral piecewise affine (PWA) system. The optimal control law between the desired acceleration and the state variables is obtained by off-line calculation. Then the adaptive cruise control is realized by locating the current state zone and applying the explicit control law of the zone. The longitudinal tracking simulation results show that the designed control strategy has good tracking effect.",

keywords = "Adaptive cruise control, Explicit model predictive control, Intelligent electric vehicle",

author = "Shumin Ruan and Yue Ma and Qi Yan",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 17th Chinese Intelligent Systems Conference, CISC 2021 ; Conference date: 16-10-2021 Through 17-10-2021",

year = "2022",

doi = "10.1007/978-981-16-6324-6_87",

language = "English",

isbn = "9789811663239",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "860--869",

editor = "Yingmin Jia and Weicun Zhang and Yongling Fu and Zhiyuan Yu and Song Zheng",

booktitle = "Proceedings of 2021 Chinese Intelligent Systems Conference - Volume II",

address = "Germany",

}

Ruan, S, Ma, Y & Yan, Q 2022, Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control. in Y Jia, W Zhang, Y Fu, Z Yu & S Zheng (eds), Proceedings of 2021 Chinese Intelligent Systems Conference - Volume II. Lecture Notes in Electrical Engineering, vol. 804 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 860-869, 17th Chinese Intelligent Systems Conference, CISC 2021, Fuzhou, China, 16/10/21. https://doi.org/10.1007/978-981-16-6324-6_87

Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control. / Ruan, Shumin; Ma, Yue; Yan, Qi.
Proceedings of 2021 Chinese Intelligent Systems Conference - Volume II. ed. / Yingmin Jia; Weicun Zhang; Yongling Fu; Zhiyuan Yu; Song Zheng. Springer Science and Business Media Deutschland GmbH, 2022. p. 860-869 (Lecture Notes in Electrical Engineering; Vol. 804 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control

AU - Ruan, Shumin

AU - Ma, Yue

AU - Yan, Qi

PY - 2022

Y1 - 2022

N2 - In order to take into account the tracking control effect and real-time performance of vehicle adaptive cruise control (ACC), a multi-objective control method based on explicit model predictive control (EMPC) is proposed; First, the model of adaptive cruise control is established. According to the predictive control theory, the multi-objective function and constraints of vehicle’s safety, tracking, economy and comfort are determined. Based on the multi parameter programming theory, the closed-loop model predictive control system based on repeated online optimization calculation is transformed into an equivalent explicit polyhedral piecewise affine (PWA) system. The optimal control law between the desired acceleration and the state variables is obtained by off-line calculation. Then the adaptive cruise control is realized by locating the current state zone and applying the explicit control law of the zone. The longitudinal tracking simulation results show that the designed control strategy has good tracking effect.

AB - In order to take into account the tracking control effect and real-time performance of vehicle adaptive cruise control (ACC), a multi-objective control method based on explicit model predictive control (EMPC) is proposed; First, the model of adaptive cruise control is established. According to the predictive control theory, the multi-objective function and constraints of vehicle’s safety, tracking, economy and comfort are determined. Based on the multi parameter programming theory, the closed-loop model predictive control system based on repeated online optimization calculation is transformed into an equivalent explicit polyhedral piecewise affine (PWA) system. The optimal control law between the desired acceleration and the state variables is obtained by off-line calculation. Then the adaptive cruise control is realized by locating the current state zone and applying the explicit control law of the zone. The longitudinal tracking simulation results show that the designed control strategy has good tracking effect.

KW - Adaptive cruise control

KW - Explicit model predictive control

KW - Intelligent electric vehicle

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U2 - 10.1007/978-981-16-6324-6_87

DO - 10.1007/978-981-16-6324-6_87

M3 - Conference contribution

AN - SCOPUS:85118121171

SN - 9789811663239

T3 - Lecture Notes in Electrical Engineering

SP - 860

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BT - Proceedings of 2021 Chinese Intelligent Systems Conference - Volume II

A2 - Jia, Yingmin

A2 - Zhang, Weicun

A2 - Fu, Yongling

A2 - Yu, Zhiyuan

A2 - Zheng, Song

PB - Springer Science and Business Media Deutschland GmbH

T2 - 17th Chinese Intelligent Systems Conference, CISC 2021

Y2 - 16 October 2021 through 17 October 2021

ER -

Ruan S, Ma Y, Yan Q. Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control. In Jia Y, Zhang W, Fu Y, Yu Z, Zheng S, editors, Proceedings of 2021 Chinese Intelligent Systems Conference - Volume II. Springer Science and Business Media Deutschland GmbH. 2022. p. 860-869. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-16-6324-6_87

Adaptive Cruise Control for Intelligent Electric Vehicles Based on Explicit Model Predictive Control

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