Multistage adaptive nonlinear control of battery-ultracapacitor based plugin hybrid electric vehicles

•Adaptive terminal sliding mode controller, sliding mode controller and finite time synergetic controller have been proposed for Battery-UC HEV.•The energy management algorithm using the state of charge has also been incorporated for the varying load.•Using Lyapunov Stability Theory, asymptotic stability of the controllers has been proved.•The comparison of proposed controllers has been done with others proposed in the literature in MATLAB.•Results have been verified by testing it on real-time hardware-in-loop setup. Plugin hybrid electric vehicles (PHEVs) are getting the attention of electric transportation market and the end-users. They comprise of smart charging mechanism and a hybrid energy storage system (HESS). In this study, a topology for HESS based on battery/ultracapacitor (UC), coupled with two bi-directional DC-DC buck-boost converters has been considered. For controlled integrated charging and smooth execution of energy management algorithm, a unidirectional DC-DC converter has been used. The mathematical model of the complete HESS with integrated charging unit for PHEV has been designed. A nonlinear controller termed as adaptive terminal sliding mode control (ATSMC) along with adaptive law has been proposed. The controller parameters have been tuned using genetic algorithm. Also an algorithm of high level control has been presented to switch between static and dynamic behaviors of the PHEV. The objective of the proposed control strategy is to adapt the unknown parameters of the system, deliver power for load well in time, output DC bus voltage regulation and smooth tracking of reference currents for the battery and UC with varying demands of the vehicle. The asymptotic stability of the system has been ensured by using Lyapunov stability theory. Finally, the energy management algorithm using the state of charge (SoC) as decisive factor is incorporated to maintain the stability of the system under varying load conditions. The performance of proposed controller has been compared with conventional sliding mode controller (SMC) and finite time synergetic controller (FTSC) using MATLAB/Simulink. The performance of the system is further verified by testing it on real-time hardware-in-loop setup.