Control Systems for Vehicle Dynamics and Stability

Modern road vehicles employ a range of control systems designed to monitor and modulate dynamic behaviour for safety, comfort and efficiency. These systems address lateral and longitudinal stability by regulating steering, braking and propulsion to maintain intended trajectories and respond to sudden disturbances. Core components include vehicle state estimation modules that infer unmeasurable variables such as sideslip angle and tyre–road friction, and decision layers that compute corrective actions in real time. Hierarchical architectures often feature a supervisory unit that assesses current and predicted states, an upper coordination layer that selects objectives (for example, yaw-rate or lateral acceleration targets) and lower actuation layers that distribute commands to brakes, drive motors and active steering mechanisms. Advances in algorithms—from model-based observers to data-driven estimators and from classical PID to model predictive control—have enabled robust performance under varying road conditions and driver inputs. Integration with vehicle-to-vehicle and vehicle-to-infrastructure communications promises further gains in predictive accuracy and cooperative stability management. The global significance of these developments is evident in reduced accident rates, greater adoption of autonomous functions and improvements in energy consumption through optimised control actions.

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Control Systems for Vehicle Dynamics and Stability publication trend

The graph below shows the total number of articles in control systems for vehicle dynamics and stability across all publications each year (not limited to Nature Index journals).

Technical terms

Model predictive control (MPC): A control strategy that solves an optimisation problem at each time step to predict and enforce desired future states while respecting system constraints.

Unscented Kalman filter (UKF): A nonlinear state estimator that propagates a set of sample points through the system model to approximate mean and covariance of predicted states.

Event-triggered control: A communication scheme that updates or transmits control data only when predefined conditions are met, reducing unnecessary bandwidth use.

Sideslip angle: The angle between a vehicle’s longitudinal axis and its actual velocity vector, indicating lateral misalignment crucial for stability assessment.

Wheel slip: The relative difference between tyre circumferential speed and vehicle ground speed, which ABS and traction systems regulate to maintain grip.

Yaw rate: The rate of rotation about the vertical axis of the vehicle, used to monitor and control directional stability.

References

1. Interacting multiple model-based ETUKF for efficient state estimation of connected vehicles with V2V communication. Green Energy and Intelligent Transportation (2023).
2. Model predictive path tracking control for automated road vehicles: A review. Annual Reviews in Control (2023).
3. Survey on Wheel Slip Control Design Strategies, Evaluation and Application to Antilock Braking Systems. IEEE Access (2020).