Research on the control strategy of electric vehicle battery and cabin thermal management system based on fuzzy PID

Aiming at the problems of regulating the comfort of the passenger cabin of electric vehicle air conditioning and improving the energy utilization, a simulation model of the battery-cabin coupling system of an electric vehicle is developed in this paper, and designs On-off, Proportional Integral-Derivative (PID), and improved fuzzy PID control strategy (IFPC) to regulate the compressor speed, respectively. Feed-forward control as well as passenger cabin comfort calculation are added to the fuzzy PID control strategy to maintain a more suitable and stable temperature in the passenger cabin under variable operating conditions. Through co-simulation, IFPC maintains the battery temperature better, automatically adjusts the cabin temperature based on past data, and provides better dynamic response to speed changes in compressor speed control. In addition, it consumes less energy. Under the simulated urban conditions, its energy consumption is 22.4% less than On-off control and 7% less than the PID control, and the COP is 32.8% and 10.6% higher than the On-off and PID controllers, separately. Accordingly, the strategy established improve the efficiency of electric vehicles.

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Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1117/12.3034195
Primary Topic
Advanced Algorithms and Applications
Type
article
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Research on the control strategy of electric vehicle battery and cabin thermal management system based on fuzzy PID

Zhiyong Duan, Zhenpeng Bai, Ahao Liu
Advanced Algorithms and Applications
article

Research on the control strategy of electric vehicle battery and cabin thermal management system based on fuzzy PID

Zhiyong Duan, Zhenpeng Bai, Ahao Liu
article en

Abstract

Aiming at the problems of regulating the comfort of the passenger cabin of electric vehicle air conditioning and improving the energy utilization, a simulation model of the battery-cabin coupling system of an electric vehicle is developed in this paper, and designs On-off, Proportional Integral-Derivative (PID), and improved fuzzy PID control strategy (IFPC) to regulate the compressor speed, respectively. Feed-forward control as well as passenger cabin comfort calculation are added to the fuzzy PID control strategy to maintain a more suitable and stable temperature in the passenger cabin under variable operating conditions. Through co-simulation, IFPC maintains the battery temperature better, automatically adjusts the cabin temperature based on past data, and provides better dynamic response to speed changes in compressor speed control. In addition, it consumes less energy. Under the simulated urban conditions, its energy consumption is 22.4% less than On-off control and 7% less than the PID control, and the COP is 32.8% and 10.6% higher than the On-off and PID controllers, separately. Accordingly, the strategy established improve the efficiency of electric vehicles.

Chang'an University (CN)
Affordable and clean energy
Openalex Percentile: Top 79%
Advanced Algorithms and Applications
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Research on the control strategy of electric vehicle battery and cabin thermal management system based on fuzzy PID — Zhiyong Duan, Zhenpeng Bai, et al. · (2024) | TGRS Research Map | TGRS