Optimizing Electric Vehicle Performance, Range and Parameter Estimation through NEDC Urban and Suburban Analysis using MATLAB

G. Ghorai, Rohit Nayak
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Abstract

This research paper focuses on electric vehicle (EV) driving range and parameter estimation, with an emphasis on analyzing the New European Driving Cycle (NEDC) urban and suburban drive cycles. By examining these drive cycles, we obtain critical data on the moments when an electric vehicle transitions between constant velocity, acceleration, and deceleration phases, which significantly affect power consumption and driving range. We investigate various techniques for parameter estimation, including battery capacity, energy consumption rates, and powertrain efficiency, essential for improving EV performance and providing realistic range expectations. Empirical experiments in diverse driving conditions contribute valuable data to refine our understanding of EV driving range and performance in different scenarios. The research underscores the role of predictive modeling, data analytics, and advanced technologies in real-time parameter estimation, offering precise and convenient range predictions to enhance user confidence.
使用 MATLAB 通过 NEDC 城市和郊区分析优化电动汽车性能、续航里程和参数估计
本文的研究重点是电动汽车(EV)的行驶里程和参数估计,重点分析了新欧洲行驶循环(NEDC)的城市和郊区行驶循环。通过研究这些驾驶循环,我们获得了电动汽车在匀速、加速和减速阶段之间转换时刻的关键数据,这些时刻对功耗和行驶里程有重大影响。我们研究了各种参数估计技术,包括电池容量、能耗率和动力总成效率,这些对于提高电动汽车性能和提供现实的续航里程预期至关重要。在不同驾驶条件下进行的实证实验提供了宝贵的数据,有助于我们更好地理解电动汽车在不同场景下的行驶里程和性能。研究强调了预测建模、数据分析和先进技术在实时参数估计中的作用,提供了精确便捷的续航里程预测,增强了用户的信心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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