Energy-efficient transportation is critical due to environmental concerns, rising fuel costs, and the shift to electric and hybrid vehicles (EVs and HEVs). Traditional braking systems waste a significant amount of energy as heat, and while regenerative braking systems recapture some energy, they lack optimization. In connected and autonomous vehicles (CAVs), there's potential to improve energy recovery during braking through better control and integration with vehicle dynamics.
Our technology maximizes energy recovery through three distinct levels of automation, utilizing advanced perception methods like RADAR, LIDAR, and multiple cameras. The first level, Advising and Filtering, provides guidance based on sensor data. The second level, Full Automation, uses an optimized braking algorithm to control the braking process for maximum energy capture. The third level, Dynamic Gear Ratio, integrates a Continuously Variable Transmission (CVT) with a fuzzy-logic controller to dynamically adjust the gear ratio between the motor and the wheels, optimizing energy recapture in real-time. Simulations using MATLAB/Simulink demonstrated significant improvements in energy recovery, with efficiency gains ranging from 24% to 61%. In urban driving conditions, the system increased vehicle range by 37.8%, showcasing its real-world potential for energy savings. This fully automated system enhances both vehicle performance and energy recovery, making it unique compared to existing technologies.
Three Levels of Automation for Regenerative Braking Optimization.