Current Status

For this study, a detailed literature survey has been carried out to arrive at specific problem identification, literature survey to investigate optimization techniques used for HESS sizing and Energy Management (EM) for EV application, converter topologies for HESS, control strategies of converters, battery modelling, and supercapacitor modelling and cell selection.

For the case study, Mahindra electric e2o smart city vehicle was chosen, and set target performance parameter for the US06 drive cycle.

Simulated battery-electric vehicle model in MATLAB-Simulink to generate energy and power request which will act as constraints of HESS size.

An integrated optimization approach is employed to optimize the size of the HESS by utilizing an computationally effective online energy management technique and minimizing parameters such as battery capacity loss, HESS mass, and the lifetime financial cost of electric vehicles.

This study proposed computationally effective real time power split mechanism strategy based on fuzzy-logic based energy management technique to distribute power effectively among two energy sources (batter and SC) in HESS.

To arrive at the optimal size of HESS (EBAT and ESC), formulated constraints, and mathematical expressions defining objective functions (battery capacity loss, lifetime financial cost of HESS and HESS mass) as a function of HESS sizing.

An effective multi-objective optimization technique, the Non-Sorted Dominated Sorting Genetic Algorithm (NSGA-III) is used to find a feasible size of series and parallel combination of supercapacitor cells for HESS.

Obtained the pareto front from NSGA-III algorithm and based on design preference, obtained most suitable solution (series and parallel combination of supercapacitor cells).

Based on this preferred solution, to validate the effectiveness of adopting the SC in ESS, A detailed comparative analysis has been carried out between proposed HESS system, battery-alone and hybrid ESS configuration controlled by fundamental EM technique in terms of battery capacity loss and life cycle cost of ESS.

Also, for optimal HESS design, this study validated the proposed efficient real-time fuzzy logic-based EM technique’s efficiency, comprehensiveness, and efficacy through simulations involving multiple driving cycles with different driving patterns/characteristic (US06, UDDS, & NEDC).

Conducted analysis and developed an innovative Partial Power Configuration (PPC) utilizing the Dual Active Bridge (DAB) as a power interface to enhance the power-density of EV powertrains based on HESS.

The proposed PPC-DAB interface undergoes comprehensive efficiency analysis, coupled with transient dynamic results, validating its potential to enhance the power density of HESS-based EV powertrains.