Approximate Globally Optimal Energy Management Strategy for Fuel Cell Hybrid Mining Trucks Based on Rule-Interposing Balance Cost Minimization

Yixv Qin (), Zhongxing Li, Guoqing Geng and Bo Wang
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Yixv Qin: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Zhongxing Li: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Guoqing Geng: School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
Bo Wang: FAW Jiefang Marketing Headquarters Qingdao Medium and Heavy-Duty Vehicle Sales Company, FAW Jiefang Automotive Co., Wuxi 214000, China

Sustainability, 2025, vol. 17, issue 4, 1-28

Abstract: Fuel cell hybrid vehicles offer significant potential in heavy-duty transportation due to their high efficiency, extended range, and zero emissions, making them a key enabler of sustainable transportation. To enhance the energy consumption economy and lifecycle economy of fuel cell hybrid mining trucks (FCHMTs) while reducing total operating costs and promoting environmental sustainability, this paper proposes an approximate globally optimal energy management strategy (EMS) based on a rule-interposing balance cost minimization strategy (AGO-BCMS). First, an FCHMT power system model is established, including degradation models for the fuel cell and battery. Then, the global optimality of dynamic programming (DP) is utilized to extract the fuel cell output characteristics under different battery states and vehicle power demands. Subsequently, optimal rules are designed and embedded into the cost minimization optimization model to plan the fuel cell output range under actual driving conditions. Simultaneously, dynamic threshold updates are performed based on vehicle driving condition phase recognition. Finally, energy distribution optimization is calculated using sequential quadratic programming (SQP). This strategy not only improves the economic viability of FCHMTs but also contributes to the broader goals of advancing sustainable transportation solutions. The proposed strategy was validated under both single round-trip and continuous operational conditions. Simulation results show that, under single round-trip conditions, the proposed strategy reduces the total operational cost by 3.13%, 4.09%, and 10.90% compared to balance cost-minimization strategies (BCMS), equivalent consumption minimization strategy (ECMS), and rule-based strategies, respectively. Under continuous operational conditions, the total cost is reduced by 3.61%, 6.63%, and 15.90%, respectively.

Keywords: fuel cell hybrid mining truck; energy management strategy; dynamic programming; cost minimization; degradation of battery and fuel cell; sustainable transportation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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