Abstract
The use of suspension preview information obtained from a quarter vehicle model (QvM) to control an active seat has been shown by the authors to be very promising, in terms of improved ride comfort. However, in reality, a road vehicle will be subjected to disturbances from all four wheels, and therefore the concept of preview enhanced control should be applied to a full vehicle model. In this paper, different preview scenarios are examined, in which suspension data is taken from all or limited axles. Accordingly, three control strategies are hypothesized—namely, front-left suspension (FLS), front axle (FA), and four wheel (4W). The former utilises suspension displacement and velocity preview information from the vehicle suspension nearest to the driver’s seat. The FA uses similar preview information, but from both the front-left and front-right suspensions. The 4W controller employs similar preview information from all of the vehicle suspensions. To cope with friction non-linearities, as well as constraints on the active actuator displacement and force capabilities, three optimal fuzzy logic controllers (FLCs) are developed. The structure of each FLC, including membership functions, scaling factors, and rule base, was sequentially optimised based on improving the seat effective amplitude transmissibility (SEAT) factor in the vertical direction, using the particle swarming optimisation (PSO) algorithm. These strategies were evaluated in simulation according to ISO 2631-1, using different road disturbances at a range of vehicle forward speeds. The results show that the proposed controllers are very effective in attenuating the vertical acceleration at the driver’s seat, when compared with a passive system. The controller that utilised suspension preview information from all four corners of the car provided the best seat isolation performance, independent of vehicle speed. Finally, to reduce the implementation cost of the “four suspension” controller, a practical alternative is developed that requires less measured preview information.
Highlights
Vehicle drivers are frequently exposed to vertical vibration over a low frequency range, which is transmitted to the driver’s seat from road roughness through the vehicle suspension and body.This vibration reduces ride comfort and can cause long-term health problems, as the human body is most sensitive to vertical vibration in the frequency range of 4–8 Hz [1,2]
This paper presents the design of three optimal FL controllers for an active seat suspension, which use measurable and low-cost preview information from the vehicle suspension states, considering hard constraints related to both allowable seat stroke and actuator force capacity
The front axle (FA)-fuzzy logic controllers (FLCs) and 4W-FLC are assumed to be composed of sub-FLCs [38], such that utilises similar preview information, but from the front-right suspension, and produces the subeach sub-FLC requires only two inputs, as shown in Figure 3b,c, respectively
Summary
Vehicle drivers are frequently exposed to vertical vibration over a low frequency range, which is transmitted to the driver’s seat from road roughness through the vehicle suspension and body. Model (QvM), which uses preview information from the vehicle suspension, was applied to control an active seat suspension Both simulation and experimental results showed that this approach can significantly attenuate the vertical vibration at the driver’s seat. This paper presents the design of three optimal FL controllers for an active seat suspension, which use measurable and low-cost preview information from the vehicle suspension states, considering hard constraints related to both allowable seat stroke and actuator force capacity. These controllers are front-left suspension (FLS-FLC), front axle (FA-FLC), and four wheels (4W-FLC). The optimal structure of each of the FLCs, including the MFs, scaling factors, and RB were sequentially designed using PSO
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