Observer-Based Predictive Torque Control with Disturbance Rejection for Multi-Motor Drives with Uncertain Load Profiles in Electric Mobility:
Observer-Based Predictive Torque Control (OBPTC) is an advanced control strategy used in multi-motor drives, specifically in the context of electric mobility systems. It is designed to efficiently control the torque output of individual motors in order to achieve desired vehicle performance while also addressing uncertainties in load profiles, which are common in real-world driving scenarios.
Here are the key principles of this control strategy:
Multi-Motor System: Electric mobility systems often utilize multiple electric motors to drive various wheels or components. In such systems, individual motor torques need to be controlled to ensure stability, traction, and overall performance.
Predictive Control: Predictive control is a control approach where the control actions are calculated by optimizing a cost function over a prediction horizon. In the case of OBPTC, the control algorithm predicts the future behavior of the system over a certain time horizon and calculates the optimal control inputs that minimize a predefined cost function.
Torque Control: The primary objective of OBPTC is to regulate the torque output of each motor. By adjusting the torque inputs to the motors, the control system can influence the vehicle's behavior, such as acceleration, deceleration, and stability.
Observer-Based Strategy: OBPTC employs an observer (estimator) to estimate the states of the system, such as the vehicle's speed, position, and motor states. These estimates are crucial for making informed control decisions and predictions about the system's future behavior.
Disturbance Rejection: Disturbances, such as changes in road conditions, gradients, or load variations, can significantly affect the vehicle's performance. OBPTC incorporates mechanisms to reject or compensate for these disturbances, enabling the vehicle to maintain desired performance even in uncertain and dynamic environments.
Uncertain Load Profiles: Electric mobility systems often encounter uncertain load profiles due to factors like changes in payload, road conditions, and terrain. OBPTC is designed to handle these uncertainties by adjusting the control inputs in real-time to maintain stability and performance.
Model-Based Approach: OBPTC relies on accurate models of the multi-motor drive system and its interactions with the vehicle dynamics. These models help predict how the system will respond to different control inputs and disturbances, facilitating optimal control decisions.
Optimization: The control algorithm optimizes the torque outputs of the motors to achieve multiple objectives simultaneously, such as minimizing energy consumption, maximizing vehicle stability, and ensuring efficient load distribution.
In summary, Observer-Based Predictive Torque Control with Disturbance Rejection for Multi-Motor Drives with Uncertain Load Profiles in Electric Mobility is a sophisticated control strategy that combines predictive control, observer-based estimation, and disturbance rejection mechanisms to efficiently manage the torque outputs of multiple motors in electric mobility systems. This approach enables the vehicles to achieve desired performance and stability even in the presence of uncertain load profiles and dynamic disturbances.