Slide Mode and Fuzzy Logic Based Powertrain Controller for the Energy Management and Battery Lifetime Extension of Series Hybrid Electric Vehicles

Chen, Zheng; Zhang, Xi; Mi, Chris

doi:10.4130/jaev.8.1425

Cited by 11 publications

(4 citation statements)

References 24 publications

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“…They are accepted to be suitable for the control of HEVs as they are suitable for multi-domain, nonlinear and time-varying systems [4,12,16]. The use of fuzzy logic controller can help circumvent the need for rigorous mathematical modeling [17].…”

Section: Control Strategies For Series Hybrid Electric Vehiclesmentioning

confidence: 99%

Modelling and fuzzy logic based control scheme for a series hybrid electric vehicle

UYSAL¹,

Altın²

2023

Journal of Energy Systems

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Ever stricter emission regulations, declining petroleum resources, increasing pollution, and global warming triggered an interest in e-mobility. Although fully electrified transportation is targeted, hybrid electric vehicles have become attractive during this transition period due to reasons such as battery challenges, range anxiety, grid capacity, and charging infrastructure. Hybrid electrical vehicles require challenging energy management systems due to the increasing number of components and energy conversions. This paper aims to introduce a simple yet effective control scheme to control the battery state-of-charge (SOC) and regenerative braking of a hybrid electric vehicle. For this purpose, a fuzzy logic controller is developed, three inputs as the SOC, driver demand, and vehicle velocity are defined. Instead of torque or power requirement, which are commonly used as controller inputs in the literature, a more straightforward method is adopted by using the accelerator and brake pedal positions. The controller manages the engine power and regenerative braking intensity. A series hybrid electric vehicle model is created in the MATLAB/Simulink environment to validate the performance of the proposed controller. The proposed controller aims to keep the SOC between 30-40% after charge depleting mode, and ensures prevention of regenerative braking at high SOC values to prevent overcharging. Simulations have been performed according to NEDC and WLTC, show that the proposed controller is able to realize design objectives.

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Section: Control Strategies For Series Hybrid Electric Vehiclesmentioning

confidence: 99%

Modelling and fuzzy logic based control scheme for a series hybrid electric vehicle

UYSAL¹,

Altın²

2023

Journal of Energy Systems

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“…It has less computation and a higher real-time performance, but it cannot achieve the global optimization. The IOCS is a method of the online optimization of power system energy allocation that mainly includes the ECMS, MPC [63,64], robust control (RC), sliding mode control (SMC) [65], and reinforcement learning (RL) [66]. The ECMS and the MPC are the two most representative methods [67].…”

Section: Instantaneous Optimization Control Strategymentioning

confidence: 99%

A Comprehensive Review on Classification, Energy Management Strategy, and Control Algorithm for Hybrid Electric Vehicles

et al. 2020

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The energy management strategy (EMS) and control algorithm of a hybrid electric vehicle (HEV) directly determine its energy efficiency, control effect, and system reliability. For a certain configuration of an HEV powertrain, the challenge is to develop an efficient EMS and an appropriate control algorithm to satisfy a variety of development objectives while not reducing vehicle performance. In this research, a comprehensive, multi-level classification for HEVs is introduced in detail from the aspects of the degree of hybridization (DoH), the position of the motor, the components and configurations of the powertrain, and whether or not the HEV is charged by external power. The principle and research status of EMSs for each type of HEV are summarized and reviewed. Additionally, the EMSs and control algorithms of HEVs are compared and analyzed from the perspectives of characteristics, applications, real-time abilities, and historical development. Finally, some discussions about potential directions and challenges for future research on the energy management systems of HEVs are presented. This review is expected to bring contribution to the development of efficient, intelligent, and advanced EMSs for future HEV energy management systems.

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“…In this paper, a philosophy is displayed by which the efficiency increases because of streamlined motor are separated from the mileage increases due to regenerative braking. In [29] a control based strategy was developed in order to improvise fuel economy and efficiency of engine of series hybrid vehicle using fuzzy logic and sliding mode control. The fuzzy logic controller has two inputs; the vehicle power demand and SOC of the battery and purpose of this controller was to increase engine and battery efficiency levels.…”

Section: Introduction Advent Of High Pace Development Of Internal Com...mentioning

confidence: 99%

Efficiency enhancement strategy implementation in hybrid electric vehicles using sliding mode control

Ibrar

Ahmad

Safdar

et al. 2023

Electrical Engineering & Electromechanics

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Introduction. Hybrid electric vehicles are offering the most economically viable choices in today's automotive industry, providing best solutions for a very high fuel economy and low rate of emissions. The rapid progress and development of this industry has prompted progress of human beings from primitive level to a very high industrial society where mobility used to be a fundamental need. However, the use of large number of automobiles is causing serious damage to our environment and human life. At present most of the vehicles are relying on burning of hydrocarbons in order to achieve power of propulsion to drive wheels. Therefore, there is a need to employ clean and efficient vehicles like hybrid electric vehicles. Unfortunately, earlier control strategies of series hybrid electric vehicle fail to include load disturbances during the vehicle operation and some of the variations of the nonlinear parameters (e.g. stator’s leakage inductance, resistance of winding etc.). The novelty of the proposed work is based on designing and implementing two robust sliding mode controllers (SMCs) on series hybrid electric vehicle to improve efficiency in terms of both speed and torque respectively. The basic idea is to let the engine operate only when necessary keeping in view the state of charge of battery. Purpose. In proposed scheme, both performance of engine and generator is being controlled, one sliding mode controllers is controlling engine speed and the other one is controlling generator torque, and results are then compared using 1-SMC and 2-SMC’s. Method. The series hybrid electric vehicle powertrain considered in this work consists of a battery bank and an engine-generator set which is referred to as the auxiliary power unit, traction motor, and power electronic circuits to drive the generator and traction motor. The general strategy is based on the operation of the engine in its optimal efficiency region by considering the battery state of charge. Results .Mathematical models of engine and generator were taken into consideration in order to design sliding mode controllers both for engine speed and generator torque control. Vehicle was being tested on standard cycle. Results proved that, instead of using only one controller for engine speed, much better results are achieved by simultaneously using two sliding mode controllers, one controlling engine speed and other controlling generator torque.

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Slide Mode and Fuzzy Logic Based Powertrain Controller for the Energy Management and Battery Lifetime Extension of Series Hybrid Electric Vehicles

Abstract: Abstract

Cited by 11 publications

References 24 publications

Modelling and fuzzy logic based control scheme for a series hybrid electric vehicle

Modelling and fuzzy logic based control scheme for a series hybrid electric vehicle

A Comprehensive Review on Classification, Energy Management Strategy, and Control Algorithm for Hybrid Electric Vehicles

Efficiency enhancement strategy implementation in hybrid electric vehicles using sliding mode control

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