This research designed an energy management system involving a battery-supercapacitor Hybrid Energy Storage System (HESS) for electric vehicles (EV). The objective is to improve the performance of the HESS by combining battery and supercapacitor features, accounting for topographical information to guarantee continuous hybridization during the drive cycle. Contour Positioning System (CPS) was used to determine the slope of the rode travelled by the vehicle. Two adaptive algorithms were designed for a rule-based controller to control the energy shared between the battery and the supercapacitor; an optimal adaptive controller and fuzzy adaptive controller. The HESS model, electric vehicle and controllers were tested using MATLAB/Simulink with three real drive cycles, namely, uphill, downhill and city tour, in three different speeds 50Km/h, 60Km/h and 70 Km/h. The results proved the controllers managed to extend battery life-cycle by reducing the stress on the battery for the drive cycles. The results were compared in terms of energy consumption for the optimal adaptive rule-based controller and fuzzy adaptive rule-based controller. The optimal adaptive rule-based controller guaranteed the HESS was able to operate continuously and extend the number of drive cycles in a wide range of speeds and road slopes.

/pdf/optimal-control-strategy-to-maximize-the-performance-of-2q9vqv9uhx.pdf

Optimal Control Strategy to Maximize the Performance of Hybrid Energy Storage System for Electric Vehicle Considering Topography Information

In this paper, the utilization of regenerative braking energy to control the speed of electric vehicle based on fuzzy logic controller is discussed. A fuzzy logic controller established is sugeno type. The output of motor controller of electric vehicle with fuzzy logic controller is acting as feedback to motor and improvement in speed of vehicle is observed. Under condition of stability and braking safety, the proposed strategy includes two types of braking force, one is regenerative and another one is frictional. So that a large amount of kinetic energy can be converted into electrical energy form and this electrical energy can be stored in the storage device like battery. This strategy is used to use the motor's regenerative braking characteristics. Modeling of FLC (fuzzy logic controller) is done under the MATLAB/Simulink software. Simulation was done with different cycles and FLC is examined with SOC (state of charge) of a battery, speed of motor and required force to drive vehicle.

Speed control of electric vehicle using fuzzy logic controller

A R T I C L E I N F O A B S T R A C T Article history: Received: 17 September, 2020 Accepted: 23 December, 2020 Online: 10 January, 2021 This research aims to investigate the energy and power management of a batterysupercapacitors Hybrid Energy Storage System (HESS) for Electric vehicles (EVs). A bidirectional DC-DC converter, a battery and a set of supercapacitors were employed to construct the parallel semi-active architecture of HESS. Two strategies of Rule-Base Linear Quadratic Regulators (R-B LQRs) were proposed to manage the power flow in HESS to reduce the overall battery stress during high demand events. The supercapacitors supply the high load demand, while the battery supplies the low load demand. The HESS, EV and the proposed controllers were simulated in a MATLAB/Simulink environment. Three standard drive cycles, namely, Urban Dynamometer Driving Schedule UDDS, New York City Cycle NYCC and Japan1015 drive cycle, were implemented to validate the controller's responses. The results of the R-B LQR controllers were compared in terms number of possible drive cycles. According to the results achieved, the proposed hybridization achieves stable response of the HESS current over the drive cycles, effectively reducing the battery’s size and extends its life-time.

/pdf/current-control-of-battery-supercapacitors-system-for-2e836avy3j.pdf

Current Control of Battery-Supercapacitors System for Electric Vehicles based on Rule-Base Linear Quadratic Regulator

Electric vehicles (EVs) are likely to be an elective vitality mode of transportation for the long run because it features an incredible capacity to decrease the utilization of petroleum based and other tall CO2 transmitting transportations powers. In this introduction, the components of the BEVs framework like a battery, control converter, impetus framework, on board charger framework, powers on vehicle were examined and a demonstration of BEV on the MATLAB-Simulink was re-enacted. This introduction basically centres on modeling, re-enactment, and examination of a BEV and its components as expressed over. Electric vehicles are potentially to be adopted for green technology applications due to their batteries' high power density and high energy density. An accurate EV model in a simulation platform is very important to design an efficient battery-powered system. In this paper, an electrical vehicle model is developed in MATLAB/Simulink. The structure of the EV is explained in detail, and an EV model is presented. The developed EV model is validated from the experiment results. From the comparison, it reveals that the developed model is capable of predicting current-voltage performance accurately. Although the model has been developed for Simple Electric vehicles, it is expected that it can be applied for other types of EV. In MATLAB results we have verified the change Velocity of electric vehicles due to change in drive cycle. 

Performance Analysis of Electric Vehicle using MATLAB/Simulink

Electric vehicles (EVs) are considered the solution for energy crisis and environment pollution in individual transportation. However, EVs are still not competitive with conventional vehicles, in terms of limitation on the driving range caused by current power battery technology. Therefore, energy efficiency is one of the most important factors for battery electric vehicles (BEVs) because they are highly dependent on the aforementioned limitations. Hence, low-speed BEVs, which are for urban transportation, can be considered a promising solution. Also, a model-based design of a real low-speed EV is presented. Given that there are no standard simulation models for these vehicle types, a novel modeling approach via Matlab/Simulink is presented and an experimental verification followed. Finally, an innovative optimization strategy is proposed through a comparative study between four basic battery types.

Modeling, simulation and performance evaluation of a low-speed battery electric vehicle

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Modeling, simulation and performance evaluation of a low-speed battery electric vehicle