李 红志, 清华大学
Creating a hardware-in-the-loop (HIL) simulation platform to accelerate the development of the Electronic Stability Program (ESP) control algorithm and decrease the high demand on a testing site due to real vehicle experiments.
Developing an HIL simulation platform for an ESP based on NI PXI, CompactRIO, and a host with all devices connected by network cables using the 15-degrees-of-freedom (DOF) vehicle model built with NI simulation modules.
An automobile ESP is an essential device used to improve automobile driving stability and safety. It integrates an antilock braking system (ABS), a traction control system (TCS), and an active yaw control system (AYC) to effectively improve the driving stability and safety of an automobile during braking, driving, and turning. The ESP controller periodically detects vehicle movement states during driving, and when danger is detected, it will promptly send commands to the braking system and engine through the controller, and reduce danger by proactively controlling the vehicle.
After conducting an in-depth investigation and considering the performance, price, and ease of implementation, we chose the NI PXI and CompactRIO platforms to build our system. We compared an xPC system, an NI PXI system, and a dSpace system and determined that the xPC system is lower in cost but not as easy to use while the dSpace system is more expensive than the PXI system even though they are similar in performance.
The hardware of the ESP HIL simulation platform consists of five parts: the host computer, target, controller, actuator, and sensor. We used the host computer to monitor the simulation process using shared variables as well as to analyze and store simulation results. In addition, the target executes the vehicle model; the controller runs control algorithms and navigates the vehicle; the actuator serves as a hydraulic control unit, braking pipeline, and a brake; and the host computer, target, and controller are connected via network cables.
The PXI system runs the vehicle model and provides reference signals to the controller. The controller captures several signals including brake signals, main cylinder pressure, four-wheel speed, steering wheel angle, horizontal acceleration, and yaw angle speed.
We used an NI PXI multifunction data acquisition (DAQ) module to acquire the analog pressure signal from all cylinders, including the main cylinder, and the digital brake signal. We also used an NI PXI arbitrary waveform generator (AWG) to output analog voltage, which represents the angle of the steering wheel, horizontal acceleration, and yaw angle speed. In addition, the NI AWG outputs four analog voltage signals and a voltage/frequency converter alters voltage into the corresponding frequency signal to simulate the speed of the four wheels. For the actuators, we used an ESP 8.0 hydraulic control unit from Bosch. The brake system consists of the braking pipeline and brakes of a Jinbei van.
The software controls the simulation start and stop through shared variables and records the data from the target in some global variables. We divided the host computer monitoring software into two main parts – simulation process monitoring and simulation data viewing. Simulation process monitoring includes the functionality of parameter restore, control simulation, real-time parameter monitoring, and input of the drivers during the simulation process. It can also configure the simulation mode, gear strategy, simulation time, initial state, and ground attachment to easily conduct simulation under all conditions. Simulation data viewing allows the user to observe and compare simulation data, play back the vehicle movement during simulation, and save and restore data.
We can use the interface to observe the curve for 70 parameters in the simulation process and store and restore simulation data. By clicking the “Simulation Playback” button on the bottom right of the window, we can graphically show the running track of the vehicle. The interface program also records the yaw angle information while conducting a real vehicle experiment and sends the information through the simulation process according to the actual time intervals, which then provides the simulation results of the vehicle response.
The target uses a vehicle model with 15 DOF to run the vehicle model. The 15 DOF include six degrees for horizontal, vertical, and positional transition and rotation; eight degrees of the rotation and vertical transition of four wheels; and one degree of rotational system.
During simulation, the target acquires the pressure signal from the main cylinder and four-wheel cylinders at 1 ms intervals to calculate the vehicle force and achieve the movement states of the vehicle. It also transfers the state parameters to the controller through the PXI-6229. At the same time, the target stores the vehicle movement state parameters in the memory and transfers data to the host computer at the end of the simulation. It also continuously detects the control signals sent from the host computer. We easily implemented all of these complicated functionalities using a parallel structure.
We also used a CompactRIO controller to run an ESP control algorithm to determine if the vehicle state is dangerous based on the received sensor signals. If danger is detected, it will control the vehicle movement and resolve the crisis.
The simulation results matched well with the results of the real vehicle experiments, which demonstrates that the HIL simulation platform can effectively simulate the vehicle movement.
Our ESP HIL simulation platform based on NI PXI and CompactRIO placed the controller in the simulation loop and allowed us to easily test the algorithm in the controller. Building the simulation workbench greatly accelerated the development of an ESP control algorithm.
Li Hong-zhi
Tsinghua University
Room 532 A, 2J15# Haidian District
Beijing, China
Tel: 010-62797118
Email: hz-li07@mails.tsinghua.edu.cn
李 红志
清华大学