Research On Energy Management Strategy Of A Series Hybrid Electric Track Vehicle

Various countries' army are actively seeking new breakthroughs in the performance of main battle tank in new century.Engineers use electric drive technology in the tank transmission system,breaking the drawbacks of mechanical transmission,so that tank's maneuverability is further enhanced.Meanwhile,a variety of high-energy electronic weapons,such as laser weapons,electromagnetic guns and electric guns,greatly improve the tank's firepower performance,and the electromagnetic armor provides greater protective performance.So the electrification of tank has become the mainstream model of development.In this paper,the electric drive system of series hybrid electric tracked vehicle is studied.Firstly,an integrated control strategy controls the transition process for the multi-speed switching mode of the engine,and dynamically adjusts the torque load of the generator according to the actual speed response of the engine.The strategy achieves the joint control of the engine-generator set,which improves the stability of their output electric power.Different engine speed working modes are also analyzed,and the multi-speed switching mode is selected for further study.Secondly,in order to ensure the power distribution results in the battery peak power range,the battery SOC estimation and peak power prediction are studied.The improved unscented Kalman filter algorithm is used to design the state estimator for the accurate estimation of SOC.The real-time prediction algorithm of the peak power is realized by considering the current,voltage and SOC constraints of the battery.Then,this paper study a rule-based energy management strategy,which make the battery packs work in the range of peak charge and discharge power,therefore the strategy could optimize the engine operating points and improve the fuel economy.The optimal energy management strategy based on the cost function is proposed,which use the cost function to evaluate the cost of fuel consumption,electricity consumption,battery life loss and enginegenerator speed fluctuation.Based on the established cost function,the strategy achieves real-time optimization.Finally,in order to verify the feasibility and real-time computing ability of the energy management strategy,a hardware-in-the-loop test platform is built,and the dSPACE realtime simulation platform and the rapidECU controller are designed,meanwhile the CAN communication interface between them is designed.The rule-based energy management strategy and the optimal energy management strategy in this paper are both verified and reliaze the design goals.