Sage Journals: Discover world-class research

Abstract

In the control of electronically controlled air suspension system (ECAS), the precision and stability of height control are important targets to measure the efficiency. In the control process of an ECAS system, the phenomenon of “overinflation,”“overdeflation,” and frequent inflating and deflating is commonly existed, which is rooted in the hysteresis characteristic of the system. Based on the bench test, the system identification and quantitative performance analysis of solenoid valves and air springs were carried out, and a refined ECAS system model was built. A PID control strategy is optimized and a state-preview height control strategy is established. AMESim and Simulink are used to build the vehicle and controller models. The accuracy of the model is verified by the comparison between the co-simulation and the field test, and the conclusion is drawn that the state preview height control strategy can improve the smoothness of the height control.

Keywords

ECAS state-preview control solenoid valve overinflation and overdeflation static and dynamic modeling co-Simulation

Get full access to this article

View all access options for this article.

References

. Pneumatic drive system dynamics. Guangdong: South China University of Technology Press, 1991. pp.53–58.

SMC (China) Cooperation. Modern practical pneumatic technology. 3rd ed. Beijing: China Machine Press, 2008.

Sun

Cai

Wang

, et al. A hybrid approach to modeling and control of vehicle height for electronically controlled air suspension. Chin J Mech Eng 2016; 29(1): 152–162.

Huang

Zhou

, et al. Nonlinear model on leveling procedure of electronically controlled air suspension. J Mech Eng 2009; 45(6): 278–283.

Chen

Huang

, et al. Dynamic modeling and characteristic simulation of charging–discharging system for electronically controlled air suspension. J Syst Simul 2011; 23(6): 1225–1228.

Zhou

Zou

, et al. Hierarchical control of ride height system for electronically controlled air suspension based on variable structure and fuzzy control theory. Chin J Mech Eng 2015; 28(5): 945–953.

Wang

Dou

Sun

, et al. Vehicle height adjustment and attitude control of electronically controlled air suspension. Trans Chin Soc Agric Mach 2015; 46(10): 335–342+356.

Xiao

Chen

Wang

, et al. Research on fuzzy self adaptive control of ECAS vehicle height adjustment system based on AMESim. Mach Des Manuf 2016; 302(4): 141–144.

Kim

Lee

. Model-based fault-tolerant control for an automotive air suspension control system. Proc IMechE, Part D: J Automobile Engineering 2011; 225(11): 1462–1480.

10.

Jiang

. Design of a vehicle height and body posture adjustment hybrid automaton of electronically controlled air suspension. Int J Adapt Control Signal Process 2021; 35: 1879–1897.

11.

Zhao

Xie

, et al. Adaptive ride height controller design for vehicle active suspension systems with uncertain sprung mass and time-varying disturbance. Int J Robust Nonlinear Control 2022; 32(10): 5950–5966.

12.

Yin

Zhao

Zhang

, et al. Body height robust control of automotive air suspension system using finite-time approach. Asian J Control 2022; 24: 859–871.

13.

Hac

. Optimal linear preview control of active vehicle suspension. In: 29th IEEE conference on decision and control IEEE, Honolulu, HI, United States, 5–7 December 1990, pp.2779–2784. New York, NY: IEEE.

14.

Sheng

. A study on the simulation of semi-active air suspension with magneto-rheological damper. Automot Eng 2015; 37(5): 560–565.

15.

Mao

. Preview control of semi-active suspension with adjustable damping based on machine vision. In: ICIEA, Online, 16–21 April 2021, pp.2158–2297. New York, NY: IEEE.

16.

Deng

Hua

. Simulation and experimental validation of damping characteristic for a valve-controlled adjustable shock absorber. Int J Veh Perform 2018; 4(2): 133–154.

17.

Kaldas

Soliman

AMA

Abdallah

, et al. Robustness analysis of the model reference control for active suspension system. SAE Int J Veh Dyn Stab NVH 2020; 4(3): 165–177.

18.

Yuan

Nguyen

Zhou

. Research on semi-active air suspensions of heavy trucks based on a combination of machine learning and optimal fuzzy control. SAE Int J Veh Dyn Stab NVH 2021; 5(2): 159–172.

19.

Lyu

Wang

, “Predictive Shift Strategy of Dual-Clutch Transmission for Driving Safety on the Curve Road Combined with an Electronic Map,” SAE Int. J. Veh. Dyn., Stab., and NVH 7(1):3–21, 2023, https://doi.org/10.4271/10-07-01-0001.

Modeling and state-preview height control of electronically controlled air suspension system based on experiment

Abstract

Keywords

Get full access to this article

References