Model Predictive Control Part 2. Vehicle Lateral Dynamic Model
Motivation
First of all, we must ask: Why do we need to establish a dynamic model for vehicle lateral control? Simply put, when a vehicle operates at higher speeds, the assumption in kinematic models (such as the bicycle model) that “The direction of tire velocity aligns with the vehicle’s orientation” no longer holds. With centripetal force increasing quadratically with speed, the total lateral force acting on the vehicle become significant. Therefore, the introduction of a dynamic model aims to establish higher-order connections to better describe the non-linear characteristics of vehicle.
Model Assumptions
To simplify the model while maintaining generality, the dynamic model is built upon the following assumptions:
1.The angle between the tire velocity direction and the vehicle’s longitudinal direction denoted as
2.The angle between the tire steering angle
3.The vehicle’s longitudinal velocity remains unchanged:
4.Neglecting the influence of road banking angles
Coordinate System
This model is established under the Front-Left-Universe (FLU) inertial coordinate system. The origin of the coordinate system is fixed at the vehicle’s center of mass, with the
Force Analysis
According to Newton’s second law, the force in the
where
The vehicle’s acceleration in the
- The acceleration caused by the movement of the vehicle in the
direction, denoted as - The centripetal acceleration of the vehicle, denoted as
Substituting
For the yaw dynamics analysis along the
where
Next, let’s analyze the lateral forces
Therefore, the slip angle of the front wheels (steering wheels)
where
Similarly, for the rear wheels (assuming they cannot steer), the slip angle is:
where
Based on these points, the lateral tire forces can be rewritten as follows:
where
Using the small angle assumption and the kinematic equations, we have:
Rearange the equation
Rewrite the above equation into matrix form
Error Dynamic Model
Setting the state variables in the dynamic model as errors will facilitate the design of subsequent feedback controllers. Therefore, define error state variables as follows:
The ideal yaw rate is given by:
The ideal lateral acceleration is:
Therefore, the lateral error
Since
From above, we obtain that
Substituting above variables into the equations, we can get
Rearange to simplify the equations
Then rewrite the dynamics in matrix form
Finally, the continuous-time error dynamics could be expressed as
where
This model represents the error dynamics of the lateral position, lateral velocity, front-wheel heading angle, and angular velocity errors. It provides a foundation for designing controllers to regulate the vehicle’s lateral motion.