Intelligent Energy Optimization of Electric Vehicles Using Coordinated Regenerative Braking and Advanced Control Strategies

Abstract: Improving energy efficiency remains a critical challenge in the development of electric vehicles (EVs), particularly under real-world driving conditions where braking events significantly influence overall energy consumption. Regenerative braking systems offer an effective solution by converting vehicle kinetic energy into electrical energy during deceleration; however, their performance is strongly dependent on braking force coordination, control strategy design, and power electronic interfaces. Previous studies have investigated braking force coordination for in- wheel motor–driven EVs using electro-hydraulic composite braking systems to enhance stability and energy recovery. Additional research has explored alternative energy recovery mechanisms such as regenerative suspension systems, demonstrating the feasibility of harvesting vibration energy to complement regenerative braking. Advanced modeling and simulation approaches have been proposed to accurately evaluate EV energy efficiency under practical driving conditions braking effectiveness. Fuzzy logic–based approaches, have shown significant potential in optimizing regenerative braking torque distribution, improving braking smoothness, and maximizing energy recovery under system uncertainties. Synchronization control strategies for distributed drive electric vehicles further contribute to coordinated regenerative braking and improved system robustness.

Keywords: Electric vehicles, regenerative braking, energy optimization, intelligent control strategies, braking force coordination, bidirectional power converters, fuzzy logic control, neural control, energy management systems