Date of Award
University Scholars Director
Dr. Jeff Keuss
First Advisor/Committee Member
Dr. John Lindberg
Second Advisor/Committee Member
Dr. Kevin Bolding
Abstract—Active suspension systems adjust the suspension components of an automobile to adapt to bumps or potholes that are encountered in the road as the vehicle is driving. These systems have the potential to improve safety, performance, and ride comfort in automobiles. An integral part of active suspension systems is a device to detect irregularities in the road. Current detection systems that are available lack either in precision, resolution, or speed. A senior design project, Dynamic Automatic Adjusting Suspension (DAAS), at Seattle Pacific University expressed a need for a high-performance road scanner that could be paired with their suspension system. The design would need to take into account problems with latency and resolution. I therefore began development of the Road Profile Sensor (RPS). The RPS was implemented through the design of a range finder that uses a linear photodiode array paired with a laser to measure distance. The distance from the sensor to the road changes as irregularities in the road are encountered, and this change in distance is measured by the RPS to determine the size of the irregularity. The proposed system runs on a soft processor core in an FPGA chip that is both a part of the DAAS system and communicates with the DAAS suspension controller. The RPS can be sampled 62 times per second and has height resolution of 4mm. With further development, the RPS has the potential to run at very high speeds in relatively low-power, low-cost FPGA’s. This design will yield much greater resolution in road scanning, which will lead to better suspension control, and a generally more reliable active suspension system. These improvements in road irregularity detection are expected to improve isolation between the road and the chassis of the vehicle, thereby improving the vehicle’s handling, versatility, and safety.
Edel, Matthew, "Road Profile Sensor: A Detection Method for Active Suspension Systems" (2014). Honors Projects. 3.