Deep Learning Based Intelligent Active Suspension Control for Heavy Trucks (DMPSO)

2021 ◽  
pp. 347-354
Author(s):  
Anis Hamza ◽  
Noureddine Ben Yahia
2020 ◽  
Vol 11 (1) ◽  
pp. 290
Author(s):  
Hakan Basargan ◽  
András Mihály ◽  
Péter Gáspár ◽  
Olivier Sename

Several studies exist on topics of semi-active suspension and vehicle cruise control systems in the literature, while many of them just consider actual road distortions and terrain characteristics, these systems are not adaptive and their subsystems designed separately. This study introduces a new method where the integration of look-ahead road data in the control of the adaptive semi-active suspension, where it is possible to the trade-off between comfort and stability orientation. This trade-off is designed by the decision layer, where the controller is modified based on prehistorical passive suspension simulations, vehicle velocity and road data, while the behavior of the controller can be modified by the use of a dedicated scheduling variable. The adaptive semi-active suspension control is designed by using Linear Parameter Varying (LPV) framework. In addition to this, it proposes designing the vehicle velocity for the cruise controller by considering energy efficiency and comfort together. TruckSim environment is used to validate the operation of the proposed integrated cruise and semi-active suspension control system.


2017 ◽  
Vol 139 (3) ◽  
Author(s):  
Yechen Qin ◽  
Feng Zhao ◽  
Zhenfeng Wang ◽  
Liang Gu ◽  
Mingming Dong

This paper presents a comprehensive comparison and analysis for the effect of time delay on the five most representative semi-active suspension control strategies, and refers to four unsolved problems related to semi-active suspension performance and delay mechanism that existed. Dynamic characteristics of a commercially available continuous damping control (CDC) damper were first studied, and a material test system (MTS) load frame was used to depict the velocity-force map for a CDC damper. Both inverse and boundary models were developed to determine dynamic characteristics of the damper. In addition, in order for an improper damper delay of the form t+τ to be corrected, a delay mechanism of controllable damper was discussed in detail. Numerical simulation for five control strategies, i.e., modified skyhook control SC, hybrid control (HC), COC, model reference sliding mode control (MRSMC), and integrated error neuro control (IENC), with three different time delays: 5 ms, 10 ms, and 15 ms was performed. Simulation results displayed that by changing control weights/variables, performance of all five control strategies varied from being ride comfort oriented to being road handling oriented. Furthermore, increase in delay time resulted in deterioration of both ride comfort and road handling. Specifically, ride comfort was affected more than road handling. The answers to all four questions were finally provided according to simulation results.


2021 ◽  
Author(s):  
Hakan Basargan ◽  
Andras Mihaly ◽  
Peter Gaspar ◽  
Olivier Sename

Sign in / Sign up

Export Citation Format

Share Document