# Enhancing electric vehicle powertrain energy efficiency using robust nonlinear control approaches

## TL;DR

This paper proposes a robust nonlinear control method to improve the energy efficiency of electric vehicle powertrains under various disturbances and uncertainties.

## Contribution

A novel robust nonlinear controller using backstepping with damping functions is introduced for electric vehicle drivetrain control.

## Key findings

- A nonlinear model of the electric vehicle system was developed to account for disturbances and uncertainties.
- The proposed controller achieved asymptotic stability and robust performance in simulations.
- The control strategy successfully optimized speed tracking and torque generation under varying conditions.

## Abstract

This paper addresses the issue of controlling the drivetrain of electric vehicles. Taking into account both internal and external system disturbances, including the vehicle’s mass, rotational friction of the shafts, wind speed, vehicle aerodynamics, road type, and slope constraints, the controller’s task is to ensure robustness in vehicle behavior. The significant dynamics of these disturbances and uncertainties in vehicle parameters have a substantial impact on vehicle performance. To overcome these challenges, a nonlinear model of the entire controlled system is developed. Subsequently, a robust nonlinear controller is designed using the damping function version of the backstepping design technique to compensate for all uncertain terms. Within this framework, two primary control loops are established. Firstly, a speed control loop is implemented to achieve precise tracking of the driver’s speed reference. Secondly, the machine current is optimized to generate maximum torque. A formal analysis based on Lyapunov stability is conducted to describe the control system’s performance. Despite parameter uncertainties, it is demonstrated that all control objectives are asymptotically achieved. Ultimately, all control objectives are validated through simulation results using Matlab/Simulink, showcasing the efficiency and robustness of the proposed control technique.