Nonlinear Optimal Control for a Flywheel and Battery-Based Powertrain of Electric Vehicles

The article proposes a nonlinear optimal control approach for integrating flywheels and batteries in the powertrain of electric vehicles. The considered power supply system for electric vehicles' traction consists of a flywheel/PMSM power source connected at its output to an AC/DC converter and of a battery pack connected at its output to a DC/DC converter. In turn, the DC outputs of the flywheel-based and battery-based power sources become inputs to a DC/AC inverter, which finally feeds the three-phase motor of the vehicle's traction system. It is proven that the state-space description of the flywheel and battery-based powertrain is differentially flat. Next, to solve the associated nonlinear optimal control problem, the state-space model of the flywheel and battery-based powertrain undergoes approximate linearization around a temporary operating point that is recomputed at each time step of the control method. The linearization relies on Taylor series expansion and the associated Jacobian matrices. For the linearized state-space model of the flywheel and battery-based powertrain, a stabilizing optimal (H-infinity) feedback controller is designed. This controller stands for the solution to the nonlinear optimal control problem under model uncertainty and external perturbations. To compute the controller's feedback gains, an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The stability properties of the control method are proven through Lyapunov analysis. The proposed nonlinear optimal control approach achieves fast and accurate tracking of reference setpoints under moderate variations of the control inputs and a minimum dispersion of energy.