Research on energy management of model predictive control based on fuzzy control algorithm optimization

Benxiang Lin; Chao Wei; Tao Liu

doi:10.1109/IC2ECS60824.2023.10493305

Research on energy management of model predictive control based on fuzzy control algorithm optimization

Benxiang Lin, Chao Wei^*, Tao Liu

^*Corresponding author for this work

School of Mechanical Engineering

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

Abstract

To further improve the efficiency of energy management strategy for heavy-duty Hybrid Electric Vehicle (HEV), taking distributed electric drive heavy-duty Hybrid Electric Vehicle (HEV) as the research object, an energy management strategy combining fuzzy control algorithm and model predictive control (MPC) was proposed, and the length of prediction time domain was optimized by fuzzy algorithm. Simulation results showed that, compared with the fixed time domain model predictive energy management strategy under CHTC-TT working condition, The average time of iteration of the energy management strategy is reduced by about 22.7%, and the fuel consumption per 100 km is reduced by about 2.3%.

Original language	English
Title of host publication	2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1040-1044
Number of pages	5
ISBN (Electronic)	9798350382426
DOIs	https://doi.org/10.1109/IC2ECS60824.2023.10493305
Publication status	Published - 2023
Event	3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023 - Hybrid, Hangzhou, China Duration: 29 Dec 2023 → 31 Dec 2023

Publication series

Name	2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023

Conference

Conference	3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023
Country/Territory	China
City	Hybrid, Hangzhou
Period	29/12/23 → 31/12/23

Keywords

Energy Management Strategy
RBF
fuzzy control algorithm
model predictive control

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IC2ECS60824.2023.10493305

Cite this

Lin, B., Wei, C., & Liu, T. (2023). Research on energy management of model predictive control based on fuzzy control algorithm optimization. In 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023 (pp. 1040-1044). (2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IC2ECS60824.2023.10493305

Lin, Benxiang ; Wei, Chao ; Liu, Tao. / Research on energy management of model predictive control based on fuzzy control algorithm optimization. 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 1040-1044 (2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023).

@inproceedings{4cba9350c720448c890d911694f1c240,

title = "Research on energy management of model predictive control based on fuzzy control algorithm optimization",

abstract = "To further improve the efficiency of energy management strategy for heavy-duty Hybrid Electric Vehicle (HEV), taking distributed electric drive heavy-duty Hybrid Electric Vehicle (HEV) as the research object, an energy management strategy combining fuzzy control algorithm and model predictive control (MPC) was proposed, and the length of prediction time domain was optimized by fuzzy algorithm. Simulation results showed that, compared with the fixed time domain model predictive energy management strategy under CHTC-TT working condition, The average time of iteration of the energy management strategy is reduced by about 22.7%, and the fuel consumption per 100 km is reduced by about 2.3%.",

keywords = "Energy Management Strategy, RBF, fuzzy control algorithm, model predictive control",

author = "Benxiang Lin and Chao Wei and Tao Liu",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023 ; Conference date: 29-12-2023 Through 31-12-2023",

year = "2023",

doi = "10.1109/IC2ECS60824.2023.10493305",

language = "English",

series = "2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1040--1044",

booktitle = "2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023",

address = "United States",

}

Lin, B, Wei, C & Liu, T 2023, Research on energy management of model predictive control based on fuzzy control algorithm optimization. in 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023. 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023, Institute of Electrical and Electronics Engineers Inc., pp. 1040-1044, 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023, Hybrid, Hangzhou, China, 29/12/23. https://doi.org/10.1109/IC2ECS60824.2023.10493305

Research on energy management of model predictive control based on fuzzy control algorithm optimization. / Lin, Benxiang; Wei, Chao; Liu, Tao.
2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 1040-1044 (2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023).

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

TY - GEN

T1 - Research on energy management of model predictive control based on fuzzy control algorithm optimization

AU - Lin, Benxiang

AU - Wei, Chao

AU - Liu, Tao

PY - 2023

Y1 - 2023

N2 - To further improve the efficiency of energy management strategy for heavy-duty Hybrid Electric Vehicle (HEV), taking distributed electric drive heavy-duty Hybrid Electric Vehicle (HEV) as the research object, an energy management strategy combining fuzzy control algorithm and model predictive control (MPC) was proposed, and the length of prediction time domain was optimized by fuzzy algorithm. Simulation results showed that, compared with the fixed time domain model predictive energy management strategy under CHTC-TT working condition, The average time of iteration of the energy management strategy is reduced by about 22.7%, and the fuel consumption per 100 km is reduced by about 2.3%.

AB - To further improve the efficiency of energy management strategy for heavy-duty Hybrid Electric Vehicle (HEV), taking distributed electric drive heavy-duty Hybrid Electric Vehicle (HEV) as the research object, an energy management strategy combining fuzzy control algorithm and model predictive control (MPC) was proposed, and the length of prediction time domain was optimized by fuzzy algorithm. Simulation results showed that, compared with the fixed time domain model predictive energy management strategy under CHTC-TT working condition, The average time of iteration of the energy management strategy is reduced by about 22.7%, and the fuel consumption per 100 km is reduced by about 2.3%.

KW - Energy Management Strategy

KW - RBF

KW - fuzzy control algorithm

KW - model predictive control

UR - http://www.scopus.com/inward/record.url?scp=85191437124&partnerID=8YFLogxK

U2 - 10.1109/IC2ECS60824.2023.10493305

DO - 10.1109/IC2ECS60824.2023.10493305

M3 - Conference contribution

AN - SCOPUS:85191437124

T3 - 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023

SP - 1040

EP - 1044

BT - 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023

Y2 - 29 December 2023 through 31 December 2023

ER -

Lin B, Wei C, Liu T. Research on energy management of model predictive control based on fuzzy control algorithm optimization. In 2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 1040-1044. (2023 3rd International Conference on Electrical Engineering and Control Science, IC2ECS 2023). doi: 10.1109/IC2ECS60824.2023.10493305

Research on energy management of model predictive control based on fuzzy control algorithm optimization

Abstract

Publication series

Conference

Keywords

UN SDGs

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