Abstract
Hybrid electric vehicles are an effective alternative to the conventional fuel engine vehicles and thus efficient and intelligent energy management is the key for establishing a significant market for the hybrid electric vehicles globally. Recent developments in the field of intelligent techniques and demand to make the energy systems intelligent have become a means to develop energy efficient hybrid electric vehicles. The energy management issue becomes vital in order to enhance the autonomy of hybrid electric vehicles and to reduce the costs. Therefore, a novel approach with intelligent techniques, to control the plug-in hybrid electric vehicles, in front of different customer profiles has been presented. This paper presents the battery performance improvement of a plug-in hybrid electric vehicle using fuzzy logic controller and neural fuzzy logic controller with battery state of charge as a deciding parameter and consequently comparing the performance of both cases. The battery state of charge and engine speed as input has been selected and based on their values the advanced controller decides the accurate torque required to be converted to energy which could be used to charge the battery and this can be achieved by controlling the forward gain value. For this, an advanced fuzzy controller and advanced adaptive nuero fuzzy inference system controller are used to decide the value of forward gain. Simulink environment is used to simulate the performance of the proposed system. This could be helpful in deciding which type of intelligent system is to be used for the power efficient operation of the hybrid electric vehicle. The results of both the control techniques are compared and the better controller is recommended for energy management of a plug-in electric vehicles. The results indicate that advanced control techniques provide the good performance and improving the fuel budget of hybrid electric vehicles.
Highlights
The automobile industry is transitioning to electric powered vehicles from the conventional combustion engine vehicles [1]
A fuzzy logic and ADAPTIVE NUERO FUZZY INFERENCE SYSTEM (ANFIS) based energy management is established for suitably managing the power distribution in plug-in hybrid electric vehicles, which is equipped with a battery based hybrid energy storage system
The fuzzy logic based battery state of charge (SOC) control and generator power could be used to improve the SOC profile and the electric mode could be used to travel on comparatively long distances
Summary
The automobile industry is transitioning to electric powered vehicles from the conventional combustion engine vehicles [1]. One of the major reasons for this transition is that a major portion of the carbon dioxide emissions comes from the conventional combustion engine vehicles. This emission is responsible for the rising air pollution levels especially in the metro cities where the number of vehicles are very high as compared to smaller cities. New Delhi is a very good example of the cities which have hugely impacted from the air pollution. There is an urgent need for an effective alternative to the conventional fuel based vehicles
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