Development of Energy-Aware Hamiltonian-Based Fixed-Time Chaos Control and Synchronisation of Brushless DC Motor for Electric Vehicle Application

• Omokhafe J. TOLA

  Author

• James G. AMBAFI

  Department of Electrical and Electronics Engineering, Federal University of Technology, Minna, Nigeria

  Author

• Emmanuel C. OBUAH

  Author

• Isah N. ABUBAKAR

  Author

• Mutiat S. YISA

  Author

Electric Vehicle (EV) Drivetrains commonly employ in electric vehicles, and Brushless DC (BLDC) motors, which are widely used for their efficiency, power density, and ease of maintenance. Their architecture, however, contains one particular fault in its operation: under certain voltage, torque, and damping conditions, they can exhibit deterministic chaos, caused by the nonlinear coupling between their electrical and mechanical states. This poses a real danger in EVs, as battery fluctuations, thermal drift and sudden changes in torque during acceleration or regenerative braking can readily drive the motor into unpredictable speed and torque oscillations, a problem that current control methods struggle to solve. Although a direct control law is not obtained from Hamiltonian energy analysis alone, such analysis helps explain the origins of this chaos. In contrast to fractional-order, fuzzy, and neural controllers, which offer only bounded or exponential convergence guarantees a critical drawback during operational faults an energy-aware, fixed-time controller based on the Hamiltonian method is proposed to suppress chaos and synchronise BLDC drives. A dimensionless chaos model is first developed, and its energy dynamics are examined to isolate the exact imbalance between energy injection and dissipation that causes chaotic behaviour. The error dynamics are then reformulated into a port-controlled Hamiltonian system. This structure enables a fixed-time control law that directly regulates the Hamiltonian gradient without requiring high-gain switching. A Lyapunov proof guarantees a strict settling-time bound defined independently of the motor's initial state. All simulations were implemented and validated in MATLAB/Simulink, with controller performance verified against the theoretical settling-time bound obtained from the Lyapunov analysis. Finally, simulation results for reference tracking and master-slave synchronisation verified the controller's performance. By unifying energy-based chaos analysis with fixed-time stability theory, this framework provides a physically interpretable control mechanism ideal for safety-critical EV applications such as torque vectoring and anti-lock braking.

• 41_Tola et al. (2026)

Copyright (c) 2026 Omokhafe J. TOLA, Garba AMBAFI, Emmanuel C. OBUAH, Isah N. ABUBAKAR, Mutiat S. YISA (Author)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.