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Self-balancing electric motorcycles have been recently developed by high-tech corporations to reaffirm their vision of “enjoying the freedom of mobility.” A stabilization system based on Inertia Wheel Pendulum (IWP) has been proven to be a potential approach to this new concept. This chapter describes the mathematical models of the motor and the vehicle. Sequentially, the effects of some key parameters onto the model are studied to properly design the reaction wheel. Moreover, IMU sensor performance with Kalman filter has been successfully implemented. PID and LQR control algorithms have been explored through simulation. Consequently, the result has indicated that the LQR controller provides more stable responses. In addition, LQR algorithm has been validated on the physical prototype in various scenarios.

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Study and Implementation of Self-Balancing Electric Motorcycle

  • 会议论文

  • 发表日期：

    2025年

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  • The Dang Phan,
  • Chau Binh Pham,
  • Cong Bang Pham

摘要

Self-balancing electric motorcycles have been recently developed by high-tech corporations to reaffirm their vision of “enjoying the freedom of mobility.” A stabilization system based on Inertia Wheel Pendulum (IWP) has been proven to be a potential approach to this new concept. This chapter describes the mathematical models of the motor and the vehicle. Sequentially, the effects of some key parameters onto the model are studied to properly design the reaction wheel. Moreover, IMU sensor performance with Kalman filter has been successfully implemented. PID and LQR control algorithms have been explored through simulation. Consequently, the result has indicated that the LQR controller provides more stable responses. In addition, LQR algorithm has been validated on the physical prototype in various scenarios.