随着新能源汽车市场渗透率的持续攀升，驱动系统的可靠性与效率愈发成为行业关注的核心。电机控制器作为驱动系统的关键部件，其控制算法性能直接影响车辆在各类工况下的动力性、经济性与平顺性。在新能源汽车常见的低速高负荷、高速巡航及急加速、急减速等典型工况中，传统矢量控制算法暴露出诸多突出问题，如转矩脉动明显、系统效率大幅下降以及动态响应存在滞后等，严重制约了整车性能与驾驶体验的提升。为此，本文提出一种基于工况识别的多模式自适应控制算法，能够针对不同工况特性实现控制策略的动态调整。经仿真分析与台架试验双重验证，该优化算法可有效平滑电机转矩输出，显著降低电机铁耗与铜耗，大幅提升驱动系统综合效率；同时，对改善整车驾驶平顺性与动力响应性具有重要作用，为新能源汽车驱动控制技术的升级提供有效解决方案。

With the continuous rise in the penetration rate of the new energy vehicle market, the reliability and efficiency of the drive system have increasingly become the core focus of the industry. As the key component of the drive system, the performance of the motor controller's control algorithm directly affects the power performance, economy, and ride comfort of the vehicle under various operating conditions. In typical operating conditions commonly encountered by new energy vehicles, such as low-speed high-load, high-speed cruising, and sudden acceleration/deceleration, the traditional vector control algorithm exhibits many prominent problems, including obvious torque ripple, significant decline in system efficiency, and lagging dynamic response, which severely restrict the improvement of vehicle performance and driving experience. To address these issues, this paper proposes a multi-mode adaptive control algorithm based on operating condition identification, which realizes dynamic adjustment of control strategies according to the characteristics of different operating conditions. Verified by both simulation analysis and bench tests, the optimized algorithm can effectively smooth the motor torque output, significantly reduce the iron loss and copper loss of the motor, and greatly improve the comprehensive efficiency of the drive system. Meanwhile, it plays an important role in enhancing the ride comfort and dynamic responsiveness of the vehicle, providing an effective solution for the upgrading of new energy vehicle drive control technology.