Non-Linear Control of Grid to Vehicle System including Hybrid Energy Storage System

Abstract

Greenhouse gas emissions and variations in the price of fossil fuels can easily be solved using plugin hybrid electric vehicles (PHEVs) that are an enthusiastic substitute for their conventional internal combustion engines. In this study, the PHEVs under consideration include a hybrid energy storage system (HESS) and a smart charging mechanism. Whereas HESS employs an ultra-capacitor (UC) as an auxiliary source and a battery with an integrated smart charger as its primary source of power to drive its traction motor. Power conditioning circuitry links each source to the DC bus. A nonlinear control scheme, called barrier function-based adaptive sliding mode control (BFASMC), is proposed for PHEVs. The barrier-functions-based adaptive law is applied to the design of the sliding mode controller, which can ensure the finite-time convergence of the system’s output variable to the predetermined region of zero. Meanwhile, the proposed adaptive law can achieve a significant reduction in chattering without needing to know in advance the upper bound of system uncertainties and disturbances. The presented controller is very resilient against the non-linearities and uncertainties of the PHEVs, and it achieves various control objectives such as tight regulation of output voltage within 0.04 seconds, precise tracking of reference currents for the UC and battery with changing vehicle demands, and Power factor correction (UPF) in Grid to Vehicle (G2V) Mode. The proposed controller has been compared with sliding mode control (SMC) and finite-time synergetic controller (FTSC) by the simulation results using MATLAB/Simulink. The MATLAB simulation results show inconsequential overshoots and undershoot at the transient’s time and smooth regulation of the DC bus voltage with minor steady-state error and extremely quick convergence.