Considering that conventional heavy-duty mining trucks equipped with centralized drive systems suffer from low transmission efficiency and limited flexibility in power distribution, this study focuses on distributed independent-drive heavy-duty mining trucks and develops energy-saving control strategies from two perspectives: drive torque control and regenerative braking. For the drive torque control, based on the principle of optimal driving efficiency, the overall efficiency of the drive motors is selected as the objective function, and an adaptive genetic algorithm (AGA) is employed to optimize the torque distribution coefficients among the axles offline. For regenerative braking, a fuzzy-control-based electromechanical braking distribution strategy and a dynamic-load-based inter-axle braking force allocation strategy are proposed. Finally, a co-simulation was conducted using MATLAB/Simulink and TruckSim based on specific open-pit mining conditions. Compared with the conventional baseline without energy-saving control, the simulation results demonstrate that under the single-cycle operation, the proposed strategy increases the driving energy utilization rate by 5.69% and achieves a braking energy recovery rate of 39.41%. Furthermore, under the full-mine cyclic operation, the proposed strategy extends the vehicle’s operational duration on a single charge by 200%. These findings demonstrate the strong potential of the proposed strategy to improve overall driving efficiency and fully exploit the regenerative braking capabilities of heavy-duty mining trucks, thereby providing theoretical support for enhancing their economic efficiency and driving range.
Huang et al. (Fri,) studied this question.
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