Electric and Hybrid Vehicle Technologies
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Abstract
Abstract
Regenerative braking in a hybrid energy storage system for a rubber-tyred gantry crane (RTG-HESS) requires a trade-off between energy recovery and battery charging stress. This study develops an energy management strategy using game theory (EMSGT) in a MATLAB/Simulink–AVL Cruise co-simulation model comprising a diesel range extender, a lithium-ion battery, and a supercapacitor. An auxiliary finite zero-sum matrix evaluates candidate power allocation policies under competing objective emphases. The matrix is solved by linear programming, and the resulting probabilities are reused heuristically as weights in a deterministic constrained allocation cost. This mapping does not establish a Nash-equilibrium guarantee for the physical controller. Under a shared 100 A battery charging limit, EMSGT achieves a recovery efficiency of 0.914, compared with 0.890 for the rule-based strategy (EMSRB), corresponding to an absolute increase of 0.024 and a relative increase of 2.70%. Its normalized battery-degradation indicator is 0.641 relative to the constrained EMSRB reference of 1.000, and its supercapacitor utilization is 0.817. Additional ECMS, parameter sensitivity, Monte Carlo, and ablation results characterize performance within the tested conditions. These co-simulation results support a trade-off between recovery and modeled charging stress; they do not constitute measured battery-lifetime extension or comprehensive braking-safety validation.
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@article{Zheng2026Braking,
title = {Braking Energy Management for a Hybrid-Powered RTG Crane Using Game Theory},
author = {Yaojie Zheng and Yan Zhao and Jianjun Tang and Xingyang Chen and Cheng Chang and Hanwu Liu and Kaicheng Yang and Yuwei Fu and Hanbin Xiao},
journal = {Applied Sciences},
year = {2026},
doi = {10.3390/app162010125},
url = {https://doi.org/10.3390/app162010125}
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