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Energy optimization strategy of vehicle DCS system based on APSO algorithm

机译:基于APSO算法的车辆DCS系统能量优化策略

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In order to improve the reliability and safety of the steer-by-wire (SBW) system, this paper presents a vehicle dual-motor coupling-drive steer-by-wire (DCS) system. However, the introduction of dual-motor will change the energy consumption of the system. Aiming at the energy consumption problem, an energy optimization strategy is proposed to improve the economic performance of the DCS system. Then, the energy optimization model of the DCS system with minimum power consumption is established based on the required torque, the rotating speed of steering wheel and the map of motor efficiency, and the adaptive particle swarm optimization (APSO) algorithm is adopted to optimize the torque distribution coefficient. Finally, combined with Matlab/Simulink, Prescan, Carsim and steering data acquisition test bench, the co-simulation is conducted under sinusoidal condition, double-lane change condition and intelligent transportation environment. The results indicate that compared with traditional single-motor SBW system and DCS system with average torque distribution, the energy consumption of the DCS system with optimized torque distribution is reduced by more than 5.2% and 4.3% under sinusoidal condition and double-lane change condition, while the corresponding values under the intelligent transportation environment are decreased by 5.2% and 7.5% respectively, which demonstrates the effectiveness of the proposed energy optimization strategy.
机译:为了提高逐线(SBW)系统的可靠性和安全性,本文介绍了车辆双电机耦合驱动驱动转向绕线(DCS)系统。然而,双电机的引入将改变系统的能量消耗。旨在旨在能源消耗问题,提出了一种能源优化策略来改善DCS系统的经济性能。然后,基于所需的扭矩,方向盘的转速和电动机效率的地图建立了具有最小功耗的DCS系统的能量优化模型,以及采用自适应粒子群优化(APSO)算法来优化扭矩分布系数。最后,结合MATLAB / SIMULINK,PRESCAN,CARSIM和转向数据采集测试台,共模在正弦状况,双车道变化条件和智能交通环境下进行。结果表明,与平均扭矩分布的传统单电机SBW系统和DCS系统相比,在正弦状况下,具有优化扭矩分布的DCS系统的能耗降低了5.2%和4.3%,双车道变化条件下降,智能运输环境下的相应值分别下降5.2%和7.5%,展示了所提出的能量优化策略的有效性。

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