In January 2026, the TRANS Research Group published its latest study, “Cross-temporal framework for driving behavior impact on electric vehicle battery health”, in Communications in Transportation Research (IF: 14.5), a top-tier SCI Q1 journal in the transportation field indexed by both SCI and SSCI. This study proposes a cross-temporal electric vehicle battery lifetime quantification and evaluation framework, termed D2B (Drive to Battery), which aims to establish a quantitative linkage between daily dynamic driving behaviors and long-term battery health states. The proposed framework presents four core contributions:
- Generalizability: Under diverse travel demands and regional environmental conditions, the framework produces ten-year battery health estimations that are comparable to those obtained from standard driving cycles, enabling accurate and effective evaluation of the impacts of heterogeneous travel patterns and driving behaviors on battery health.
- Quantifiability: More stable driving behaviors can extend battery service life by approximately 10% over a ten-year timescale; in contrast, under high-intensity ride-hailing scenarios, an equivalent level of battery degradation may occur within only five years.
- Interpretability: The framework provides a practically valuable and interpretable analytical basis for personalized battery lifetime assessment under heterogeneous travel patterns, and can efficiently support decision-making in algorithm development, battery insurance pricing, and other eco-driving strategies through simulation-based evaluation.
- Transportation-Energy Integration: By coupling transportation travel scenarios with vehicle energy systems across all stages of the framework, the proposed framework ensures that battery health assessment reflects real-world electric vehicle usage conditions.
The first author of the paper is Hao Qi, a PhD student (Class of 2024) in the TRANS research group. The corresponding author is Professor Shiqi Ou. Co-authors include Associate Professors Yahui Jia and Yuan Lin from South China University of Technology, as well as Professor Zhixia Li from the University of Cincinnati, USA. This work was supported by the National Key R&D Program of China and the Guangdong Provincial Talent Introduction Team Program.