Optimal Force Distribution for Active and Semi-active Suspension Systems
Abstract: The development needs of handling and ride vehicle dynamic characteristics are constantly evolving, crucial for safety and comfortable commute since many active safety and driver assistance systems depend on these characteristics. Ride improvements enhance passenger comfort, which plays a significant role in quality and brand value. Chassis and suspension systems greatly influence these vehicle dynamic characteristics. These systems should provide stability, high precision and a high degree of adaptive performance with quick response time. One of the ways to achieve these demands is by incorporating mechatronics suspension systems. Semi-active and fully active mechatronics suspension systems offer passengers a more comprehensive range of vehicle characteristics in terms of driving experience than vehicles with purely mechanical suspension systems. The efficient implementation of mechatronics suspension systems depends on the controller type and how its commands are realised. A typical control strategy is to decide a desired behaviour on the vehicle body and realise that behaviour with the help of the semi-active or active actuators. This work focuses on the realisation of the modal coordinate controller commands that counteracts the undesired body motions. The commands are in vehicle body coordinates with respect to the COG of the vehicle. The biggest challenge is to translate these counteracting forces and torques into semi-active damper vertical forces. This challenge is addressed with different algorithms with different levels of complexity and capability. The complexity ranges from the linear system of equations to real-time optimisation. Essentially, the algorithms will fragmentise and distribute the centralised command among different actuators and finally realise them back as close as commanded by taking the actuator and other physical limitations into account. This work also focuses on developing relative weights tuning methods, which play a significant role in the cost function formation and optimisation solution. The algorithms are evaluated in three different road conditions to incorporate typical driving environments related to primary and secondary rides. The enhancements in the ride performance are visualised by comparing against the existing methodology. The conclusions strongly support the optimisation-based force allocation algorithm over the existing method. It enables significant improvements in the ride performance and a high degree of flexibility by efficiently distributing commands among four actuators, which results in utilising the full potential of the semi-active dampers.
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