An Active Seat Controller with Vehicle Suspension Feedforward and Feedback States: An Experimental Study

Abstract

Active seat suspensions can be used to reduce the harmful vertical vibration of a vehicle's seat by applying an external force using a closed loop controller. Many of the controllers found in the literature are difficult to implement practically, because they are based on using unavailable or difficult and costly measurements. This paper presents both simulation and experimental studies of five novel, simple, and cost-effective control strategies to be used for an active seat suspension in order to improve ride comfort at low frequencies below 20 Hz. These strategies use available and measurable feedforward (preview) information states from the vehicle secondary suspension, as well as feedback states from the seat suspension, together with gains optimised to minimise the occupant vibration. The gains were optimised using a genetic algorithm (GA), with a fitness function based on the seat effective amplitude transmissibility (SEAT) factor. Constraints on the control force and the seat suspension stroke were also included in the optimisation algorithm. Simulation and laboratory experimental tests were carried out to assess the performance of the proposed controllers according to the ISO 2631-1 standard, in both the frequency and time domains with a range of different road profiles. The experimental tests were performed using a multi-axis simulation table (MAST) and a physical active seat suspension configured as a hardware-in-loop (HIL) simulation with a virtual linear quarter vehicle model (QvM). The results demonstrate that the proposed controllers substantially attenuate the vertical vibration at the driver's seat compared with both a passive and a proportional-integral-derivative (PID) active seat suspension and thus improve ride comfort together with reducing vibration-linked health risks. Moreover, experimental results show that employing both feedforward information and feedback vehicle body and seat acceleration signals in the controller provides isolation performance gains of up to 19.5 dB over the human body sensitivity frequency range and improves the ride comfort in terms of the SEAT factor and the weighted root mean square (RMS) seat acceleration by at least 25% when compared with a passive system, irrespective of vehicle forward speed.

A multi-objective optimization method based on NSGA-II algorithm and entropy weighted TOPSIS for fuzzy active seat suspension of articulated truck semi-trailer

“…Where Z s and Z c are the seat and cabin travel, respectively and Z s , max is the maximum allowable seat travel which was assumed to be 45.0 mm. 38…”

“…While in modelling, all 12 variables related to membership functions and rule base for the controller are also considered. The maximum gain for the output is 1500 N, 38 the amount of load ( M L ) is between 5000 and 30,000 kg, the location of the load ( L L ) is between 4 m from the end of the trailer to the centre of mass and 6 m from the front of the trailer to the centre of mass. In the case of springs, the stiffness can change in the range of 50% of the initial value ( k t 1 : 6 ).…”

A Systematic Literature Review of Various Control Techniques for Active Seat Suspension Systems

“…In addition, a preview information was obtained from the wheels, front left suspension and front axle, which was optimized by fuzzy logic controller to cope up with friction and actuator constraints [85]. State feedback of the seat suspension and feedforward of the vehicle suspension based on preview information were implemented in [86]. In general, the preview controller can guarantee a good performance in terms of vertical vibration attenuation.…”

Analysis of Metrological Requirements in Occupational Health and Safety Regulations Related to the Emerging Risk of Exposure to Vibrations

“…Again, the measuring system will be affected by the influences mentioned above, and the lack of information might affect the efficiency of the damping system. Other investigations suggest employing available measurements together with measurements or information from the secondary vehicle suspension (spring and damper) [42].…”