Adaptive Nonlinear Control of Unified Model of Fuel Cell, Battery, Ultracapacitor and Induction Motor Based Hybrid Electric Vehicles

Abstract

The public awareness about global warming, emission of green-house gases and depletion of natural resources like oil and natural gas, are the main factors due to which fuel cell hybrid electric vehicles (FHEVs) have attained importance in automotive industry. Hard driving conditions like steep areas, slippery roads and rough terrains boost up the nonlinearities present in vehicle's model. The considered unified mathematical model of FHEV is based on fuel cell as a primary source, ultracapacitor and battery as storage units as well as the induction motor dynamics. The variations in parameters like resistance, capacitance, inductance and the nonlinearities of the dynamical system have also been considered. Three adaptation based nonlinear controllers namely adaptive terminal sliding mode, adaptive terminal synergetic and adaptive synergetic controllers have been proposed for the regulation of DC bus voltage along with speed tracking when subjected to European extra urban driving cycle. Lyapunov stability theory has been used to ensure global asymptotic stability of the system. Proposed controllers have been simulated on MATLAB/Simulink, where their comparison has been presented with each other and with recently proposed nonlinear controllers in the literature. Furthermore, ATSMC has further been implemented on real-time microcontroller hardware in the loop setup. The experimental results show that it provides better performance.INDEX TERMS Hybrid electric vehicles, adaptive terminal sliding mode control (ATSMC), adaptive terminal synergetic control (ATSC), adaptive synergetic control (ASC), hardware in the loop.

Renewable Energy Based Smart Grid Construction Using Hybrid Design in Control System with Enhancing of Energy Efficiency of Electronic Converters for Power Electronic in Electric Vehicles

“…A GA-based fuzzy logic controller has been developed to increase the performance as well as fuel economy of fuel cell-based HEVs [18]. To manage power as well as maintain level of charge in battery, an adaptive fuzzy logic based controller for fuel energy management as well as battery-based HEVs was utilised [19]. To increase battery performance and prevent battery as well as fuel cell degradation, a predictive controller method has been introduced [20].…”

Optimization of BLDC-based electric vehicles: Vehicle dynamics modelling through dual-motor approach and designing a novel augmented TLBO algorithm for PID control

“…Besides, there are some other constraints of two-wheeler EVs, such as limited energy storage of battery pack and their effective utilization, limited speed, limited range, high initial cost and the proper choice of electric motor [1,2]. EVs utilize different types of the motor such as Induction Motor (IM) [3], Switched Reluctance Motor (SRM) [4], DC motor [5], Permanent Magnet Synchronous Motor (PMSM) [6], BLDC [7] etc. Among all these motors, IM and BLDC drive for EVs are widely used in a commercial vehicle.…”

Real-Time Implementation and Control of Multi-Source Electric Vehicle Traction Motor under Various Drive Conditions

“…Considering the real-time hardware implementation of power flow regulation from multiple energy sources, adaptive, non-linear control of a hybrid electric vehicle (HEV) with a fuel cell-BU-supercapacitor (SC) hybrid source was proposed in [22]. The authors adopted a rule-based energy management to regulate the power flow from three sources.…”