Abstract: In the field of electric vehicles, single-speed and multi-speed dual-motor electric axle architectures have certain potential to improve vehicle performance, but the problem of energy consumption optimization is prominent. In this paper, a real-time estimation of motor efficiency and dynamic torque distribution strategy based on Kalman filter are proposed. As an efficient state estimation algorithm, extended Kalman filter (EKF) can fuse noisy measurement data to accurately extract motor operating status information. By constructing an extended Kalman filter observation model of motor efficiency-speed-torque, the efficiency characteristics of dual motors can be accurately estimated online. Combined with the dynamic programming algorithm, the torque of the dual motors is distributed with the goal of optimal system efficiency. Actual vehicle road tests have shown that the strategy can save 3.3% of electricity consumption compared to the proportional allocation strategy.

Key words: electric drive axle; energy management; Kalman filter

摘要： 在电动汽车领域，单挡与多挡双电机电驱桥架构对提升车辆性能有一定潜力，但能耗 优化问题突出。文章创新性地提出基于卡尔曼滤波的电机效率实时估计与动态扭矩分配策略。 电机运行易受传感器测量、内部电磁等噪声干扰，而扩展卡尔曼滤波（EKF）作为高效状态 估计算法，能融合含噪测量数据，精准提取电机运行状态信息。通过构建电机效率-转速-扭矩 的扩展卡尔曼滤波观测模型，可在线精确估算双电机效率特性。结合动态规划算法，以系统 效率最优为目标分配双电机扭矩。实车道路试验显示，该策略相较于等比例分配策略，电耗 节能达 3.3%。

关键词: 电驱桥；能量管理；卡尔曼滤波