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      Determination of the Performance Characteristics of a Traction Battery in an Electric Vehicle

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          Abstract

          Electric vehicles are the most innovative and promising area of the automotive industry. The efficiency of a traction battery is an important factor in the performance of an electric vehicle. This paper presents a mathematical model of an electric truck, including modules for the traction battery to determine the depth of battery discharge during the operation of the electric truck, a traction electric system for the electric truck and a system for calculating traction forces on the shaft in electric motors. As a result of the modelling, the charging and discharging currents of an accumulator battery in a real cycle of movement in peak and nominal modes of operation in electric motors and at different voltages of the accumulator battery are determined. A functional scheme of a generalized model of the electric vehicle traction electrical equipment system is developed. An experimental battery charge degree, torques of asynchronous electric motors, temperature of electric motors and inverters, battery voltage and the speed of electric motors have been measured and analysed. The developed complex mathematical model of an electric vehicle including a traction battery, two inverters and two asynchronous electric motors integrated into an electric portal bridge allowed us to obtain and study the load parameters of the battery in real driving cycles. Data were verified by comparing simulation results with the data obtained during driving.

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          Temperature dependent ageing mechanisms in Lithium-ion batteries – A Post-Mortem study

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            The transport sector as a source of air pollution

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              Sustainability analysis of the electric vehicle use in Europe for CO2 emissions reduction

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                Author and article information

                Contributors
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                Journal
                WEVJAU
                World Electric Vehicle Journal
                WEVJ
                MDPI AG
                2032-6653
                February 2024
                February 12 2024
                : 15
                : 2
                : 64
                Article
                10.3390/wevj15020064
                9154c646-dd17-4cab-97e8-dc4ed9a9194e
                © 2024

                https://creativecommons.org/licenses/by/4.0/

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