Regenerative power systems are designed to recuperate the otherwise lost energy during braking and no throttle conditions. This is achieved by using excess mechanical energy of the motor, to convert kinetic energy into electrical energy and then direct it back to the battery. As a result, regenerative power systems have the capability to improve energy efficiency and extend the driving range of electric vehicles.

This regenerative power project was established through a systematic and interconnected application of software, electronics, and mechanical components. The drive system consists of a brushed DC motor, motor controller and throttle. A circuit board monitors the state of the drive system and determines when appropriate conditions occur to initiate regenerative power processes. These conditions involve no throttle applied, the presence of revolutions per minute at the motor shaft and the battery not being already at full capacity. When such conditions are met, a sub circuit running between the DC motor and the battery will switch on and convert the output of the motor to appropriate charging conditions. Thus, achieving the regenerative nature of the system. To communicate the status and performance of the system dynamics, a combination of Raspberry Pi technology and Programmable System On-Chip (PSoC) controller is used to monitor the system. The Raspberry Pi generates a user interface, outlining the mode, revolutions per minute (RPM) and power generated to the battery.

Further work would involve adjusting the system from a bench testing set up to an integration with the Vespa vehicle. The project has outlined an in depth understanding on specifications of an electric drive system, as well as the electronic design of regenerative power control. The design hurdles, performance tuning as well as integration limits during the design and integration process provided significant skill developed, which is versatile in many electrical systems. Overall, the development of such a system provides a promising insight into the future of electrical automotive systems and our ability to optimise these systems.