# A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
## 4 Roll Stability Control in Road Vehicles
### Experimental Validation of Roll Stability for Road Vehicles  
#### 4.3.1 HIL Experiment Tests  
HIL testing is an efficient and reliable validation method that is widely used for performance evaluation of active rollover prevention control systems. Through HIL testing, researchers can simulate real-world road conditions in a laboratory environment and optimize control strategies without compromising driving safety [108]. HIL testing relies on virtual-physical interaction technology, coupling actual controllers with high-fidelity vehicle dynamic models in real time, enabling the control strategies to undergo rigorous testing in an environment that closely mimics real-vehicle conditions. A typical HIL testing platform consists of a real-time simulation engine, controller hardware, actuator simulation modules, sensor signal simulation, and data acquisition and analysis systems, providing a comprehensive validation of active rollover prevention control strategies [109]. The real-time simulation engine runs high-precision vehicle dynamic models (such as CarSim, TruckSim, dSPACE, or MATLAB/Simulink) to simulate vehicle responses under various conditions; the controller hardware (e.g., ESC, active suspension, or active steering controllers) executes the rollover prevention strategies; actuator simulation modules replicate the dynamic responses of braking, suspension, or steering systems; sensor signal simulation generates virtual signals for IMUs, wheel speed, steering angle, etc., to match real-world conditions; and the data acquisition and analysis system records test data in real time, evaluating the stability, robustness, and real-time performance of the control strategies. In recent years, HIL testing has been widely used to assess the effectiveness of roll stability control strategies. As shown in Figure 5a, [PERSON] et al. [14] built an HIL platform with steer/brake-by-wire and PXI systems, verifying that their TV-NMPC controller maintained the LTR below 0.8 and outperformed traditional NMPC in yaw, sideslip, and roll control. As shown in Figure 5b, [PERSON] et al. [26] used a TruckSim-based HIL setup to validate an integrated steering-suspension controller, which ensured stable control under dynamic conditions. [PERSON] et al. [77] employed dSPACE-based HIL to test cargo-laden vehicles, confirming that a variable-weight controller effectively limited the RI, yaw rate, and sideslip at high speeds and adhesion. Furthermore, as shown in Figure 5c, [PERSON] et al. [11] developed a PXI-based HIL system with a 0.001 s control cycle, where a Nash controller reduced the path error by 15% and improved the roll stability by 20%. Finally, as shown in Figure 5d, [PERSON] et al. [24] constructed a dual-host HIL platform to evaluate steer-by-wire chassis control, which showed superior performance in rollover prevention and stability at speeds of up to 80 km/h under standard testing conditions. The main advantages of HIL testing lie in its high safety, high repeatability, and low cost, allowing for the iterative optimization of control strategies without relying on real-vehicle testing. Additionally, HIL testing enables researchers to assess controller performance under extreme driving conditions, such as high-speed sharp turns or emergency evasive maneuvers, which is crucial for enhancing vehicle active safety. However, HIL testing still faces certain challenges. Firstly, the requirements for high-precision dynamic modeling and real-time computational capabilities are substantial, as it is essential to ensure that the simulation models accurately reflect the dynamic characteristics of the real vehicle. Secondly, the precise simulation of sensor signals remains a research challenge, as delays and errors in different sensors may affect the reliability of the test results.