Optimal Predictive Torque Distribution Control System to Enhance Stability and Energy Efficiency in Electric Vehicles

This article presents a novel approach to address the critical issues of stable rotation and energy efficiency in electric vehicles (EVs). To achieve these objectives, we propose a comprehensive control system that leverages the power of optimization through optimal predictive control methods. The central idea revolves around minimizing the predicted tracking error for future time steps by intelligently determining control inputs. In this innovative approach, we emphasize the dynamic adjustment of weight coefficients and optimization of wheel torque to strike a delicate balance between energy consumption and enhanced vehicle stability. The result is an adept controller that not only ensures vehicle stability but also significantly reduces energy consumption. Given the inherent limitations of electric motors, especially in terms of torque during vehicle operation, and the growing importance of energy conservation, our method tailors weight coefficients to generate optimal wheel torque. This ensures that the electric motors operate within their power range, thereby minimizing energy consumption and extending the overall efficiency of EVs. The combination of stable rotation and energy efficiency offered by this control system represents a promising step forward in the realm of electric vehicles, making them more sustainable and environmentally friendly while maintaining the high standards of performance and safety that consumers expect.

Automated summary

This article presents a novel approach using optimal predictive control methods to address the issues of stable rotation and energy efficiency in electric vehicles. By dynamically adjusting weight coefficients and optimizing wheel torque, the proposed control system achieves a balance between energy consumption and vehicle stability, resulting in stable rotation and significant reduction in energy consumption.