Research on Energy-Saving Control of Automotive PEMFC Thermal Management System Based on Optimal Operating Temperature Tracking

Qi Jiang, Shusheng Xiong, Baoquan Sun, Ping Chen, Huipeng Chen and Shaopeng Zhu ()
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Qi Jiang: College of Energy Engineering, Zhejiang University, Hangzhou 310012, China
Shusheng Xiong: College of Energy Engineering, Zhejiang University, Hangzhou 310012, China
Baoquan Sun: China FAW Group Corporation, Changchun 130000, China
Ping Chen: Power Machinery & Vehicular Engineering Institute, College of Energy Engineering, Zhejiang University, Hangzhou 310058, China
Huipeng Chen: Information Engineering College, Hangzhou Dianzi University, Hangzhou 311305, China
Shaopeng Zhu: College of Energy Engineering, Zhejiang University, Hangzhou 310012, China

Energies, 2025, vol. 18, issue 15, 1-25

Abstract: To further enhance the economic performance of fuel cell vehicles (FCVs), this study develops a model-adaptive model predictive control (MPC) strategy. This strategy leverages the dynamic relationship between proton exchange membrane fuel cell (PEMFC) output characteristics and temperature to track its optimal operating temperature (OOT), addressing challenges of temperature control accuracy and high energy consumption in the PEMFC thermal management system (TMS). First, PEMFC and TMS models were developed and experimentally validated. Subsequently, the PEMFC power–temperature coupling curve was experimentally determined under multiple operating conditions to serve as the reference trajectory for TMS multi-objective optimization. For MPC controller design, the TMS model was linearized and discretized, yielding a predictive model adaptable to different load demands for stack temperature across the full operating range. A multi-constrained quadratic cost function was formulated, aiming to minimize the deviation of the PEMFC operating temperature from the OOT while accounting for TMS parasitic power consumption. Finally, simulations under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) conditions evaluated the OOT tracking performance of both PID and MPC control strategies, as well as their impact on stack efficiency and TMS energy consumption at different ambient temperatures. The results indicate that, compared to PID control, MPC reduces temperature tracking error by 33%, decreases fan and pump speed fluctuations by over 24%, and lowers TMS energy consumption by 10%. These improvements enhance PEMFC operational stability and improve FCV energy efficiency.

Keywords: PEMFC; fuel cell vehicles; thermal management; model predictive control; temperature control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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