Modeling and Simulation of Electric Vehicle to Optimize Its Cost and Range

Kaushik, Shivangi

doi:10.35940/ijeat.e7819.088619

Cited by 12 publications

(3 citation statements)

References 2 publications

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“…The parameters Kev and Tev values are considered as 0.333 and 1, respectively, from theoretical calculations using formulas described in reference [44]. The primary purpose of this method is to maximize the use of renewable energy supplies while reducing reliance on fossil fuel plants for a clean and green environment [45][46][47].…”

Section: Loadmentioning

confidence: 99%

Contingency Analysis of a Grid Connected EV's for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme

et al. 2022

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After over a century of internal combustion engines ruling the transport sector, electric vehicles appear to be on the verge of gaining traction due to a slew of advantages, including lower operating costs and lower CO2 emissions. By using the Vehicle-to-Grid (or Grid-to-Vehicle if Electric vehicles (EVs) are utilized as load) approach, EVs can operate as both a load and a source. Primary frequency regulation and congestion management are two essential characteristics of this technology that are added to an industrial microgrid. Industrial Microgrids are made up of different energy sources such as wind farms and PV farms, storage systems, and loads. EVs have gained a lot of interest as a technique for frequency management because of their ability to regulate quickly. Grid reliability depends on this quick reaction. Different contingency, state of charge of the electric vehicles, and a varying number of EVs in an EV fleet are considered in this work, and a proposed control scheme for frequency management is presented. This control scheme enables bidirectional power flow, allowing for primary frequency regulation during the various scenarios that an industrial microgrid may encounter over the course of a 24-h period. The presented controller will provide dependable frequency regulation support to the industrial microgrid during contingencies, as will be demonstrated by simulation results, achieving a more reliable system. However, simulation results will show that by increasing a number of the EVs in a fleet for the Vehicle-to-Grid approach, an industrial microgrid’s frequency can be enhanced even further.

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Section: Loadmentioning

confidence: 99%

Contingency Analysis of a Grid Connected EV's for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme

et al. 2022

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“…Although the results have contributed significantly to the development of knowledge about IWM-EV, the results are still weak and questionable. This is because the tests conducted on IWM-EV capabilities are still limited to simulationbased tests [6], [8], [20] and HILS methods [14], [21][22][23] that require some simplification, justification, and assumptions during the tests. It is common knowledge that justification and assumptions may inaccurately reflect the data and likely result in inaccurate predictions [24].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Testing of In-Wheel Motor Based Electric Vehicle in Longitudinal Direction

Razak,

Ahmad,

Che Hasan

et al. 2023

Int. J. Automot. Mech. Eng.

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This paper presents an investigation into the performance of in-wheel motor (IWM) based electric vehicles (IWM-EV) in the longitudinal direction. The design of IWM-EV is an innovation of the conventional go-kart vehicle with slightly modifications in steering, suspension, and braking system, which then makes use three-phase permanent magnet synchronous in-wheel motor (PMSM-IWM) at both of the rear axle wheels. An extension of that is a simulation of IWM-EV vehicle using a 5-degree-of-freedom vehicle longitudinal model that has been developed by incorporating PMSM-IWM as a drive wheel located at the rear axles. Using the simulation, vehicle dynamic control in the longitudinal direction-based Proportional-Integral-Derivative (PID) controller has also been strategized. As the intention to confirm the capability of the IWM-EV, experimental studies-based real IWM-EV hardware have been conducted. Three dynamic tests that generalized from SAE standard SAE J866-199908, namely acceleration performance at the level pavement (include acceleration tests and acceleration then braking tests) and road gradient tests at constant speeds of 10, 15 and 20 km/h, were used as the testing method. The performance areas evaluated were vehicle body speed, wheel speed, distance travel experienced by the vehicle, IWMs current, drive torque as well as the battery voltage capacity used by the vehicle. The finding indicate that the simulation results and experimental data are similar with less than 5 % error. The outcomes from this study will be considered in the design optimization of a torque vectoring control in the next research study.

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“…Whale optimization algorithm (WOA) is used to optimize the gain parameters of PI controllers and adjust their gains values (Kp and Ki) in correspondence to deviations of EV speed and torque [8]. Energy consumption of the dynamic model of an electric vehicle is examined and the corresponding graph is simulated for the New European Driving Cycle (NEDC) and worldwide harmonized light vehicle test procedure (WLTP) [9]. The vehicle driving range is affected by increased energy consumption at high speeds, large loads, and battery discharge capacity.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modelling of vehicle drivetrain to predict energy consumption

Ramasamy

Kumar

Chinnasamy

2022

IJEECS

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Nowadays, <span>many firms have started producing electric vehicles (EVs). One of the biggest challenges to broad acceptance of electric vehicles is their limited range EVs. Forecasting future energy usage is one of the way to calculate the driving range. In this paper, a simulation model of the drivetrain has been developed to evaluate the energy flow of a vehicle for the given torque and speed conditions. The energy consumption of an electric vehicle is determined by the vehicle's attributes. Road torque, road speed, motor model, motor controller model, battery model, and PI controller are the primary components of the model. The overall resistive force offered by the vehicle, as well as energy consumption owing to resistive force during motoring and regeneration has been validated through the simulation results. Here, the vehicle model, Mercedes Benz Class C Saloon has been considered</span>.

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Modeling and Simulation of Electric Vehicle to Optimize Its Cost and Range

Cited by 12 publications

References 2 publications

Contingency Analysis of a Grid Connected EV's for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme

Contingency Analysis of a Grid Connected EV's for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme

Dynamic Testing of In-Wheel Motor Based Electric Vehicle in Longitudinal Direction

Mathematical modelling of vehicle drivetrain to predict energy consumption

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