Optimized Energy Consumption of Electric Vehicles with Driving Pattern Recognition for Real Driving Scenarios

• Published in: Algorithms Vol. 18; no. 4; p. 204
• Main Authors: Moulik, Bedatri, Kaur, Sanmukh, Ijaz, Muhammad
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2025
• Subjects: Accuracy; Analysis; Automobiles, Electric; Classification; Data collection; Distribution costs; Driving; Driving conditions; driving pattern recognition; Electric vehicles; Energy conservation; Energy consumption; Energy efficiency; Energy management; Energy management systems; Energy use; Fuel cells; Fuzzy logic; Hybrid vehicles; Neural networks; Optimization; Optimization techniques; Pattern recognition; Quadratic programming; Real time; representative driving cycles; Roads & highways; Sensitivity analysis; Strategic planning (Business); Traffic; Traffic speed; United Kingdom; Wavelet transforms; United Kingdom

Energy management strategies (EMS) in the context of electric or hybrid vehicles can optimize the available energy by minimizing consumption. Most optimization-based EMS are not real-time-applicable for an accurate estimation of future consumption. The performance of these strategies also strongly d...