Rahul Sohan Gupta
Department of Mechanical Engineering
National Institute of Technology
Surathkal, Karnataka - 575025
Email: rahulgupta.221me244@nitk.edu.in
Revuri Sai Datta Praneeth
Department of Mechanical Engineering
National Institute of Technology
Surathkal, Karnataka - 575025
Email: rsdp.221me343@nitk.edu.in
Dharmesh Raikwar
Department of Mechanical Engineering
National Institute of Technology
Surathkal, Karnataka - 575025
Email: dharmeshraikwar.221me117@nitk.edu.in
It has been identified that the RBS is widely used in hybrid vehicles (HV) and electric vehicles (EV). Therefore, this chapter is going to mainly focus on the use of regenerative brakes in EVs and electric hybrid vehicles to understand the general concept of the RBS. Regenerative braking generates electric energy from kinetic energy by reversing the procedure that forces a car to move forward. In electric vehicles, a battery pack is used to provide power to the motor or multiple motors to generate torque so that vehicles can move forward by using rotational force on wheels. Regenerative brakes turns the kinetic energy into electric energy at first and then mechanical energy that ensures the spin of wheel and axles. The RBS utilises the energy of spinning wheels to reverse the direction of generating electricity, such as to the direction of the battery from the electric motor or motors. In this context, drivers need to apply pressure on the brake pedal or remove the foot from the accelerator pedal to activate the RBS. Thus, the electric motor in the RBS turns into an electric generator to store energy rather than wasting all kinetic energy as heat. RBS also assists in slowing down vehicles as wheels commute energy to rotate the electric motor’s shaft.
As per the studies, when a motor runs due to external forces, it is defined as an electric generator. This fundamental concept has been applied in the “regenerative braking system”. In this context, a flywheel is utilised in the RBS to reverse the direction of energy generation in terms of turning an electric motor into an electric generator. As per the studies a “regenerative braking system” reduces fuel consumption by approximately 33% by converting kinetic energy into electric and mechanical energy. The utilisation of a single gear and direct drive transaxle in the RBS can maximise the efficiency of regenerative braking. Similarly, the engine needs to be disengaged with the drive wheels of vehicles while applying the regenerative brakes to eliminate ther energy loss due to engine friction. Furthermore, reducing the operation time of brakes can expand the life span of the brakes. Thus, the efficiency of RBS also reduces the maintenance and repair costs by reducing the application time to slow down moving vehicles. It has been recognised that the RBS increase the driving range up to 11-22% based on the RBS parameters and “drive cycle settings” such as energy consumption.
Extended driving range for electric vehicles (EVs):
The mechanism of capturing the kinetic energy and sending it back to the battery pack of EVs as electric energy can comprehensively enhance the driving range of vehicles. According to scientific estimation, the RBS can potentially extend the driving range of EVs up to hundreds of miles in a year. It not only enhances the driving range of EVS or hybrid cars but also reduces the charging time as well.
Theory:
Consider a simple circuit with four switches. The battery and the combination of armature winding and backemf are the machine. The circuit comprises switches Q1, Q2, Q3, and Q4, which are power electronic switches. During driving mode, Q1 and Q4 are on, allowing current flow from the battery through the machine. During regenerative braking, when the brakes are applied, the switches change states, causing the machine to become a higher energy state, leading to the battery being charged.
Parameters:
To simulate this, we need four switches, a battery, a machine, a resistor, and a capacitor. The machine chosen is a 5 HP machine with specific parameters. The battery chosen is a lithium-ion battery with an initial state of charge set to 50%.
Step Sign:
For inputs, a step signal is used. Negative values represent braking mode, while positive values represent acceleration mode.
Pulse Generator:
Pulse signals are generated to control the switches. The duty cycle and frequency are adjusted to simulate realistic switching behavior.
Simulation:
The simulation is run for six seconds. The battery is observed to charge and discharge based on the input signal.
Capacitance and Inductance:
Input Signal (Low Torque):
Machine Specifications:
Battery State of Charge (SOC): The battery SOC represents the percentage of charge remaining in the battery. During the simulation, the SOC varies based on the charging and discharging cycles induced by the regenerative braking system. When the vehicle decelerates and regenerative braking occurs, the battery SOC increases as it receives energy from the machine. Conversely, during acceleration, the battery discharges, causing the SOC to decrease.
Armature Current and Field Current: These parameters represent the electrical currents flowing through the machine's armature winding and field winding, respectively. During regenerative braking, the machine operates in generator mode, producing electrical current that flows back into the battery. The armature current reflects this flow of current from the machine to the battery, while the field current remains relatively constant, governing the machine's operation.
Electrical Torque: Electrical torque signifies the rotational force exerted by the machine's electrical components. In regenerative braking, the machine generates torque in the opposite direction of motion to facilitate energy conversion. This electrical torque contributes to the deceleration of the vehicle and the generation of electrical energy for battery charging.
Machine Speed: The speed of the machine, typically measured in radians per second (rad/s), provides insights into its rotational dynamics. During regenerative braking, the machine's speed decreases as it converts kinetic energy into electrical energy. This decrease in speed correlates with the vehicle's deceleration and the effectiveness of regenerative braking in recovering energy.
In conclusion, the simulation of the regenerative braking system using MATLAB/Simulink has yielded promising results, indicative of its effectiveness in recovering energy during vehicle deceleration. Through meticulous parameter selection and precise modeling, we have demonstrated the system's ability to seamlessly transition between acceleration and braking modes, efficiently harnessing kinetic energy for battery charging. The comprehensive analysis of key performance metrics, including battery state of charge, armature and field currents, electrical torque, machine speed, and energy flows, has provided valuable insights into the system's behavior. These results showcase the system's capacity to optimize energy utilization and enhance overall vehicle efficiency.
Furthermore, the successful integration of the simulated regenerative braking system underscores its potential for real-world application in electric vehicles, contributing to sustainable transportation solutions and reducing environmental impact. The findings of this study lay a solid foundation for further research, development, and optimization of regenerative braking technology in pursuit of greener and more energy-efficient mobility solutions. In light of the positive outcomes achieved in this study, it is evident that regenerative braking systems hold immense promise for revolutionizing the automotive industry and fostering a cleaner, more sustainable future.
As we move forward, continued exploration and refinement of regenerative braking technology will be instrumental in realizing its full potential and driving the transition towards a greener, more sustainable transportation ecosystem.
As executive members of IEEE NITK, we are extremely grateful for the opportunity to learn and work on this project under the prestigious name of IEEE NITK Student Chapter. We would like to extend our heartfelt thanks to IEEE for providing us with the necessary funds to complete this project successfully.
Report prepared on May 5, 2024, 1:38 p.m. by:
Report reviewed and approved by Nikesh Shetty [Piston] on May 10, 2024, 7:29 a.m..