# Adaptive Cruise Control for Intelligent City Bus Based on Vehicle Mass and Road Slope Estimation
## 4 Simulation and Experiment Results
### Experiment Test Bases on HIL  
The HIL simulation is illustrated in Figure 18 and it adopts the hierarchical control strategy. The upper level mainly includes the Real-Time System (RTS) which can guarantee the real-time performance of HIL simulation. The Host PC can download the proposed control strategy programs to ECU, and the vehicle dynamic model runs in PXI. The lower level mainly means the braking system and the driving system, as shown in Figure 19, they can implement driving and braking functions when receiving the signals from the upper level by CAN communication. In the braking system, the proportional valve and the relay valve can adjust the brake pressure according to the received desired brake signal. Similarly, the desired torque signal is transported to EM controller to adjust the driving force.  
Figure 17: The error of the mass estimation.  
Figure 18: The structure of HIL test bench.  
During the driving cycle, when the pneumatic braking system works, the proportional valve starts to pressurize the brake chamber to achieve the braking and the pressure can be acquired by pressure sensor.  
The driving cycle of the HIL test is the same as the simulation. Figure 20 is the vehicle longitudinal velocity test result from 535 s to 720 s. It can be seen that the estimated velocity with EKF control strategy follows the desired velocity well. In contrast to this, the velocity result without EKF control strategy has obvious errors with the desired velocity. This is because the bus is running in the second zone, as described in Figure 10, and the real vehicle mass is 18 tons while the mass in the control strategy without EKF is 14 tons and the large mass error making the inaccurate results. Therefore, the HIL test results are agree with the simulation results.  
Figure 19: Photo of the HIL test bench.  
Figure 20: The result of vehicle velocity.  
Figure 21 shows the change of braking force at 535 s to 720 s of the whole ACC process. The desired force comes from the output of MPC+EKF strategy. The actual force is obtained from the force sensor of the HIL test bench. It can be seen that the actual force has some shake when the desired force is zero, but when braking occurs, the actual braking force follows the desired well. Figure 22 shows the change of braking pressure in the same time period. Similar to braking force, the desired pressure comes from simulation and the actual pressure comes from the pressure sensor. It can be seen that the actual pressure has a certain delay to the desired one due to mechanical delays. Overall, the simulated pressure can reflect the actual brake pressure.  
The adjustment result of EM torque is shown in Figure 23. Similarly to the pressure control, the desired EM torque is calculated from the control strategy and the actual torque is obtained from the EM in the HIL test bench. We can see the actual torque follows the desired torque well and there is a certain delay between the desired torque and the actual torque as described in Section 2.1.  
Figure 21: The adjustment results of braking torque.  
Figure 22: The adjustment results of braking pressure.  
The HIL test results show that the tracking ability and the braking capacity can be guaranteed during the ACC process. The proposed EKF + MPC control strategy can work in the actual condition.