Scholarlink

<p>Energy-efficient electric transportation systems reduce power consumption while increasing the runtime on a single battery charge. Operating at a lower flux level can improve the efficiency of an electric vehicle drive. However, simply reducing the flux level may cause drive instability. As a result, this work proposes an enhanced flux optimization technique to improve the performance of the sensorless induction motor drive at low speeds to minimize losses through appropriate flux-weakening for the drive. Flux optimization uses constraints and boundaries on critical variables such as stator current and stator voltage. The drive’s performance is compared with existing methods and constant rated rotor flux. These include less parameter sensitivity due to the state transformation’s parameter independence and easier flux-weakening control using the maximum torque per flux controlling variable. Unlike existing flux optimization techniques, this method does not involve the solution of the parameter-dependent equation or utilizing a look-up table. Both simulation and experimental testing validate the proposed scheme’s performance for a 5.5&#xa0;kW IM. Compared to the existing methods, the result of the proposed flux optimization algorithm demonstrates its superiority in both low and high-speed zones, with better performance and robustness against motor parameter variation.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Maximum torque per flux strategy for induction machines

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月2日

查看全文
  • Marcin Morawiec,
  • Lelisa Wogi

摘要

Energy-efficient electric transportation systems reduce power consumption while increasing the runtime on a single battery charge. Operating at a lower flux level can improve the efficiency of an electric vehicle drive. However, simply reducing the flux level may cause drive instability. As a result, this work proposes an enhanced flux optimization technique to improve the performance of the sensorless induction motor drive at low speeds to minimize losses through appropriate flux-weakening for the drive. Flux optimization uses constraints and boundaries on critical variables such as stator current and stator voltage. The drive’s performance is compared with existing methods and constant rated rotor flux. These include less parameter sensitivity due to the state transformation’s parameter independence and easier flux-weakening control using the maximum torque per flux controlling variable. Unlike existing flux optimization techniques, this method does not involve the solution of the parameter-dependent equation or utilizing a look-up table. Both simulation and experimental testing validate the proposed scheme’s performance for a 5.5 kW IM. Compared to the existing methods, the result of the proposed flux optimization algorithm demonstrates its superiority in both low and high-speed zones, with better performance and robustness against motor parameter variation.