دوره 15، شماره 3 - ( 6-1404 )
جلد 15 شماره 3 صفحات 4810-4796 |
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Ansari Laleh A, shojaeefard M H. Modeling and Comparative Analysis of the Impact of Driving Cycles on Battery State of Charge Performance and Electric Vehicle Driving Range. ASE 2025; 15 (3) :4796-4810
URL: http://www.iust.ac.ir/ase/article-1-707-fa.html
URL: http://www.iust.ac.ir/ase/article-1-707-fa.html
Modeling and Comparative Analysis of the Impact of Driving Cycles on Battery State of Charge Performance and Electric Vehicle Driving Range. Automotive Science and Engineering. 1404; 15 (3) :4796-4810
چکیده: (907 مشاهده)
The escalating proliferation of electric vehicles (EVs) as a pivotal solution to address energy consumption and air pollution challenges within the transportation sector necessitates a comprehensive understanding of the factors influencing their performance and driving range. Among these factors, driving patterns exert a direct and significant impact on energy consumption and battery state. This study aims to quantify the influence of diverse driving cycles on the performance of an electric vehicle, specifically the Audi e-tron 50. Utilizing Simcenter Amesim software, a longitudinal vehicle dynamics model, coupled with an equivalent circuit model (ECM) for the lithium-ion battery, was developed for simulation purposes. The vehicle's performance was evaluated under five distinct driving cycles, including global standards (WLTC, NEDC, HWFET) and two real-world driving cycles recorded in Tehran (Route1, Route2). Key parameters such as state of charge (SoC), depth of discharge (DoD), battery temperature, and estimated driving range were analyzed. The results revealed a significant impact of driving cycles on all investigated parameters. Driving cycles characterized by higher speeds and accelerations (e.g., WLTC and HWFET) led to increased specific energy consumption, accelerated temperature rise, and a notable reduction in estimated driving range (with the lowest range observed in WLTC). Conversely, milder urban driving cycles (particularly Route1) resulted in improved energy efficiency, minimal thermal stress, and the highest estimated driving range. These findings underscore the critical importance of considering real-world and localized driving patterns for accurate performance evaluation, range estimation, and the development of optimized energy management strategies in electric vehicles.
نوع مطالعه: پژوهشي |
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