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<p>Electric vehicles (EVs) face significant challenges in maximizing operational range, primarily governed by battery energy capacity. However, this range is profoundly influenced by driver behaviour and route-specific dynamics. Persistent discrepancies between manufacturer-quoted ranges and real-world performance underscore the limitations of traditional test protocols in reflecting modern usage patterns. Driving behaviours vary considerably across vehicle categories, requiring tailored protocols. In regions such as India, local variations in traffic and infrastructure hinder standardization. Precise range prediction, combined with battery durability and warranty assessments, necessitates the incorporation of realistic usage data. Therefore, the development of appropriate usage templates is critical for the sustainability of the EV industry. This review explores the creation of EV-specific usage templates, evaluating their features and applicability. By optimizing profiles for moderated accelerations and regime-aware controls, such cycles curtail cyclic degradation mechanisms like lithium loss and active material fade by 15–25%, bolstering lifecycle reliability; concurrently, they facilitate battery management system (BMS) refinements that diminish thermal runaway probabilities by 10–15%, elevating overall safety margins in EV deployments. It offers insights into promoting EV adoption via improved testing frameworks that enhance efficiency, reliability, and safety in sustainable transportation. Moreover, data from 2024 to 2025 studies indicate 15–30% real-world range reductions under cold conditions and variable loads, highlighting the demand for climate-adaptive cycles. Enhancements in reliability through optimized profiles can prolong battery life by 20–40%, while mitigating safety hazards such as thermal runaway by up to 15%. Drive cycle optimization directly contributes to EV reliability by minimizing cyclic degradation and to safety by enabling better BMS tuning, reducing fault risks and extending component longevity.</p>

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Refining EV drive patterns: effects on range, reliability enhancement, and safety assurance

  • 期刊论文

  • 发表日期：

    2026年3月9日

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  • Utkarsh Alset,
  • Datta Chavan,
  • Snehal Andhale,
  • Panchshila Pillewar

摘要

Electric vehicles (EVs) face significant challenges in maximizing operational range, primarily governed by battery energy capacity. However, this range is profoundly influenced by driver behaviour and route-specific dynamics. Persistent discrepancies between manufacturer-quoted ranges and real-world performance underscore the limitations of traditional test protocols in reflecting modern usage patterns. Driving behaviours vary considerably across vehicle categories, requiring tailored protocols. In regions such as India, local variations in traffic and infrastructure hinder standardization. Precise range prediction, combined with battery durability and warranty assessments, necessitates the incorporation of realistic usage data. Therefore, the development of appropriate usage templates is critical for the sustainability of the EV industry. This review explores the creation of EV-specific usage templates, evaluating their features and applicability. By optimizing profiles for moderated accelerations and regime-aware controls, such cycles curtail cyclic degradation mechanisms like lithium loss and active material fade by 15–25%, bolstering lifecycle reliability; concurrently, they facilitate battery management system (BMS) refinements that diminish thermal runaway probabilities by 10–15%, elevating overall safety margins in EV deployments. It offers insights into promoting EV adoption via improved testing frameworks that enhance efficiency, reliability, and safety in sustainable transportation. Moreover, data from 2024 to 2025 studies indicate 15–30% real-world range reductions under cold conditions and variable loads, highlighting the demand for climate-adaptive cycles. Enhancements in reliability through optimized profiles can prolong battery life by 20–40%, while mitigating safety hazards such as thermal runaway by up to 15%. Drive cycle optimization directly contributes to EV reliability by minimizing cyclic degradation and to safety by enabling better BMS tuning, reducing fault risks and extending component longevity.