I led the development of an Inertial Measurement Unit (IMU)-based torque vectoring system designed to enhance the SR-4’s cornering performance by over 20%. The IMU data, including acceleration and yaw rate, was integrated into a custom control algorithm that dynamically adjusted the power delivered to each wheel during cornering. This resulted in better traction control and vehicle stability, especially when navigating sharp turns or rough terrain.

To achieve optimal torque distribution, I designed mathematical models that correlated steering angle, yaw rate, and overall vehicle dynamics. Using these models, I developed a PID (Proportional-Integral-Derivative) control algorithm to minimize yaw rate error and maintain vehicle stability. The model was tested extensively through simulations in MATLAB/Simulink before being implemented on the hardware.

The implementation of the torque vectoring system required the development of embedded C/C++ code for Tiva C Series microcontrollers, which controlled the motor speed and torque based on real-time sensor input. The microcontroller firmware was responsible for processing the IMU data and applying the appropriate control signals to the motor controllers.
The motor speed and position feedback were acquired through encoders, which were configured to provide high-resolution data to the microcontroller. This information was used to maintain precise control of the torque delivered to each wheel, optimizing the vehicle's handling in all driving conditions.

To ensure efficient communication between the various subsystems, I integrated the torque vectoring system with the car's Controller Area Network (CAN) bus. The CAN bus allowed for seamless data exchange between the motor controllers, IMU, and other essential components of the solar car, enabling coordinated control of the entire powertrain.