A framework integrates map data, Bidirectional LSTM driver behavior modeling, and quasi-steady physics-based energy consumption to generate personalized BEV velocity, power, and SOC profiles that capture individual patterns across urban, freeway, and hilly routes.
Investigating long- term vehicle speed prediction based on BP-LSTM algorithms,
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Personalized electric vehicle energy consumption estimation framework that integrates driver behavior with map data
A framework integrates map data, Bidirectional LSTM driver behavior modeling, and quasi-steady physics-based energy consumption to generate personalized BEV velocity, power, and SOC profiles that capture individual patterns across urban, freeway, and hilly routes.