Presence of an alternative energy source along with the Internal Combustion Engine (ICE) in Hybrid Electric Vehicles (HEVs) appeals for optimal power split between them for minimum fuel consumption and maximum power utilization. Hence HEVs provide better fuel economy compared to ICE based vehicles/conventional vehicle. Energy management strategies are the algorithms that decide the power split between engine and motor in order to improve the fuel economy and optimize the performance of HEVs. This paper describes various energy management strategies available in the literature. A lot of research work has been conducted for energy optimization and the same is extended for Plug-in Hybrid Electric Vehicles (PHEVs). This paper concentrates on the battery powered hybrid vehicles. Numerous methods are introduced in the literature and based on these, several control strategies are proposed. These control strategies are summarized here in a coherent framework. This paper will serve as a ready reference for the researchers working in the area of energy optimization of hybrid vehicles.

The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuelefficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors' role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability. Keywords Hybrid electric vehicle Á Hybrid energy storage system Á Architecture Á Traction motors Á Bidirectional converter Abbreviations and symbols ABS Antilock braking system AC Alternating current ADTR Antidirectional-twin-rotary ADVISOR Advanced vehicle simulator ANN Artificial neural network ASCI Auto-sequential commutated mode singlephase inverter BEV Battery electric vehicle BLDC Brushless DC motor CD Charge depletion CDFIM Cascaded DFIM CF-qZSI Current-fed quasi-ZSI CMPPT Centralized MPPT CS Charge sustaining CSI Current source inverter CS-PMSM Compound-structure PMSM CVT Continuous variable transmission DC Direct current DFIM Doubly fed induction motor DMPPT Distributed MPPT DRM Double-rotor machines DTC Direct torque control e-CVT Electronic continuous variable transmission EM Electric motor EMS Energy management system EREV Extended range electric vehicle ESS Energy storage system EV Electric vehicle FC Fuel cell

Energy management strategies significantly influence the fuel efficiency of hybrid electric vehicles. They play a crucial role in splitting the power between two sources, namely, engine and the battery. Power split between these two intelligently will enhance the fuel economy and regulates the power flow. Power split between engine and motor depends on state of charge (SOC) of battery, power required at the wheels, and engine's operating range. Various parameters of power train are considered to control the toggling between engine and battery. To achieve parameter optimization, genetic algorithm is practised to realize the optimal performance. A modified SOC estimation algorithm is employed with different battery models to analyze the vehicle performance. The battery models with internal resistance only and combinations of 1RC and 2RC are used. Parameter optimization over different battery models with modified SOC estimation algorithm is performed in different situations and a comparative study is elaborated.

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Summary This paper presents the design and implementation of a photovoltaic‐integrated shunt active power filter (SAPF) to improve the power quality and to generate clean power. The system uses adaptive neuro‐fuzzy inference system (ANFIS)‐based maximum power point tracking and control of synchronous reference frame theory–based SAPF. Various control schemes are implemented in MATLAB and then validated in real‐time using FPGA‐based computation engine of OPAL‐RT 4510. Control techniques built around the artificial neural network, fuzzy logic control, and ANFIS are compared for balanced and unbalanced loads on parameters like total losses with/without compensation, voltage drop, power factor, and total harmonic distortion.

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