FUZZY LOGIC CONTROL FOR ENERGY MANAGEMENT SYSTEM OF A HYBRID ELECTRIC VEHICLE

The Hybrid Electric Vehicle (HEV) electric motor is typically powered by a battery pack through power electronics. The fuel consumption in HEV is already lower compared to conventional vehicle. However, there will be a need to control the distribution of torque between the engine and electric motor to further minimize the fuel consumption. With reference to this issues, the purpose of this project is to create a complete HEV using a MATLAB/Simulink tool. From the model created, it will be equipped with a controller for energy management system. The method used is by taking the driver command, the state of charge (SOC) of the battery, the vehicle speed, percentage of throttle and engine efficiency as inputs, a fuzzy logic control for parallel HEV has been developed in a controller to effectively control the torque distribution between Internal Combustion Engine (ICE) and electric motor which is known as In-Wheel Motor (IWM). This research also discusses the methodology for designing a base vehicle model using MATLAB/Simulink. Prior to modelling HEV model, the base vehicle model was validated in terms of the fuel consumption to verify the model. The verified built base model will then be modified to become HEV model by virtually installing IWM at the rear wheels together with a controller inside the trunk. The proposed energy management strategy is implemented on a parallel HEV model and it is then simulated to a selected drive cycles. Since the distribution of torque in HEV model is varied according to the rules set, the fuel consumption is reduced significantly as compared with conventional base vehicle model. The simulation results reveal that, the HEV model built from conventional vehicle model has a significant improvement of 23% in terms of fuel economy as well as maintaining battery SOC within its operation range

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Cooperative Control of Regenerative Braking and Antilock Braking for a Hybrid Electric Vehicle

A new cooperative braking control strategy (CBCS) is proposed for a parallel hybrid electric vehicle (HEV) with both a regenerative braking system and an antilock braking system (ABS) to achieve improved braking performance and energy regeneration. The braking system of the vehicle is based on a new method of HEV braking torque distribution that makes the antilock braking system work together with the regenerative braking system harmoniously. In the cooperative braking control strategy, a sliding mode controller (SMC) for ABS is designed to maintain the wheel slip within an optimal range by adjusting the hydraulic braking torque continuously; to reduce the chattering in SMC, a boundary-layer method with moderate tuning of a saturation function is also investigated; based on the wheel slip ratio, battery state of charge (SOC), and the motor speed, a fuzzy logic control strategy (FLC) is applied to adjust the regenerative braking torque dynamically. In order to evaluate the performance of the cooperative braking control strategy, the braking system model of a hybrid electric vehicle is built in MATLAB/SIMULINK. It is found from the simulation that the cooperative braking control strategy suggested in this paper provides satisfactory braking performance, passenger comfort, and high regenerative efficiency

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

Comparison between unipolar and bipolar single phase grid-connected inverters for PV applications

An inverter is essential for the interfacing of photovoltaic panels with the AC network. There are many possible inverter topologies and inverter switching schemes and each one will have its own relative advantages and disadvantages. Efficiency and output current distortion are two important factors governing the choice of inverter system. In this paper, it is argued that current controlled inverters offer significant advantages from the point of view of minimisation of current distortion. Two inverter switching strategies are explored in detail. These are the unipolar current controlled inverter and the bipolar current controlled inverter. With respect to low frequency distortion, previously published works provide theoretical arguments in favour of bipolar switching. On the other hand it has also been argued that the unipolar switched inverter offers reduced switching losses and generates less EMI. On efficiency grounds, it appears that the unipolar switched inverter has an advantage. However, experimental results presented in this paper show that the level of low frequency current distortion in the unipolar switched inverter is such that it can only comply with Australian Standard 4777.2 above a minimum output current. On the other hand it is shown that at the same current levels bipolar switching results in reduced low frequency harmonics

Comparison between unipolar and bipolar single phase grid-connected inverters for PV applications

An inverter is essential for the interfacing of photovoltaic panels with the AC network. There are many possible inverter topologies and inverter switching schemes and each one will have its own relative advantages and disadvantages. Efficiency and output current distortion are two important factors governing the choice of inverter system. In this paper, it is argued that current controlled inverters offer significant advantages from the point of view of minimisation of current distortion. Two inverter switching strategies are explored in detail. These are the unipolar current controlled inverter and the bipolar current controlled inverter. With respect to low frequency distortion, previously published works provide theoretical arguments in favour of bipolar switching. On the other hand it has also been argued that the unipolar switched inverter offers reduced switching losses and generates less EMI. On efficiency grounds, it appears that the unipolar switched inverter has an advantage. However, experimental results presented in this paper show that the level of low frequency current distortion in the unipolar switched inverter is such that it can only comply with Australian Standard 4777.2 above a minimum output current. On the other hand it is shown that at the same current levels bipolar switching results in reduced low frequency harmonics

Intelligent energy management agent for a parallel hybrid vehicle

This dissertation proposes an Intelligent Energy Management Agent (IEMA) for parallel hybrid vehicles. A key concept adopted in the development of an IEMA is based on the premise that driving environment would affect fuel consumption and pollutant emissions, as well as the operating modes of the vehicle and the driver behavior do. IEMA incorporates a driving situation identification component whose role is to assess the driving environment, the driving style of the driver, and the operating mode (and trend) of the vehicle using long and short term statistical features of the drive cycle. This information is subsequently used by the torque distribution and charge sustenance components of IEMA to determine the power split strategy, which is shown to lead to improved fuel economy and reduced emissions

FUZZY LOGIC CONTROL FOR ENERGY MANAGEMENT SYSTEM OF A HYBRID ELECTRIC VEHICLE

The Hybrid Electric Vehicle (HEV) electric motor is typically powered by a battery pack through power electronics. The fuel consumption in HEV is already lower compared to conventional vehicle. However, there will be a need to control the distribution of torque between the engine and electric motor to further minimize the fuel consumption. With reference to this issues, the purpose of this project is to create a complete HEV using a MATLAB/Simulink tool. From the model created, it will be equipped with a controller for energy management system. The method used is by taking the driver command, the state of charge (SOC) of the battery, the vehicle speed, percentage of throttle and engine efficiency as inputs, a fuzzy logic control for parallel HEV has been developed in a controller to effectively control the torque distribution between Internal Combustion Engine (ICE) and electric motor which is known as In-Wheel Motor (IWM). This research also discusses the methodology for designing a base vehicle model using MATLAB/Simulink. Prior to modelling HEV model, the base vehicle model was validated in terms of the fuel consumption to verify the model. The verified built base model will then be modified to become HEV model by virtually installing IWM at the rear wheels together with a controller inside the trunk. The proposed energy management strategy is implemented on a parallel HEV model and it is then simulated to a selected drive cycles. Since the distribution of torque in HEV model is varied according to the rules set, the fuel consumption is reduced significantly as compared with conventional base vehicle model. The simulation results reveal that, the HEV model built from conventional vehicle model has a significant improvement of 23% in terms of fuel economy as well as maintaining battery SOC within its operation range

A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed

Intelligent energy management in hybrid electric vehicles

The modelling and simulation approach is employed to develop an intelligent energy management system for hybrid electric vehicles. The aim is to optimize fuel consumption and reduce emissions. An analysis of the role of drivetrain, energy management control strategy and the associated impacts on the fuel consumption with combined wind/drag, slope, rolling, and accessories loads are included.<br /