Regenerative braking system in electric Two wheelers

This survey has provided a comprehensive review of regenerative braking technology for electric two-wheelers, covering physical principles, hardware topologies, control strategies, energy storage interaction, stability considerations, and evaluation methodologies. Key findings are: (1)   Fuzzy logic control offers the best embedded feasibility-to- performance ratio for near-term commercial E2W applications, typically improving energy recovery by 15–22% over rule-based methods. (2)  SoC-aware and thermally constrained regeneration is essential for battery longevity; naive maximum-regeneration policies accelerate capacity fade. (3)  Two-wheeler pitch dynamics impose hard torque limits that must be explicitly encoded in any regeneration controller. (4)  Deep reinforcement learning shows the highest potential gains (25–35% improvement) but requires significant advances in embedded inference before commercial deployment. (5)  Standardised evaluation frameworks and comprehensive real- world datasets remain critical unmet needs for the field. The Smart Regenerative Braking Optimization System developed in the accompanying M.Tech project directly addresses several of these gaps through real-time fuzzy logic control, IMU-based pitch compensation, and CAN-bus BMS integration on an embedded platform.

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