Implementation of velocity optimisation strategy based on preview road information to trade off transport time and fuel consumption for hybrid mining trucks

Implementation of velocity optimisation strategy based on preview road information to trade off transport time and fuel consumption for hybrid mining trucks

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Unmanned mining is one of the essential fields of mining technology at present. Therefore, optimisation with known driving speed cycle for fuel economy, emissions, driveability, and more is no longer exclusive, the optimal velocity trajectory based on road information has been studied. Given that both fuel consumption and transport time influence transport costs of mining trucks, an energy management strategy (EMS) based on velocity optimisation is proposed and illustrated on a series hybrid electric mining truck in this study. The vehicle speed and SOC are adopted as state variables. Then two-scale dynamic programming is applied to calculate optimum velocity trajectory and power distribution. Simulation results reveal that the weighting coefficients of transport time and fuel economy can be optimally distributed for the different design requirements. Compared to the results under the known driving speed cycle, the proposed EMS can enhance fuel economy by 26.59% under the guarantee of same transport time, or transport time can be reduced by 42.4% without sacrificing the fuel consumption. Therefore, the proposed velocity optimisation strategy can reduce transport costs for mining enterprises significantly.


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