While semi-active suspensions help improve the ride comfort and road holding capacity of the vehicle, they tend to be reactive in nature and thus leave a lot of room for improvement. Incorporating road preview data allows these suspensions to become more proactive rather than reactive and helps achieve a higher level of performance. A lot of preview-based control algorithms in literature tend to require high computational effort to arrive at the optimal parameters thus making it difficult to implement in real time. Other algorithms tend to be based upon lookup tables which classify the road input into different categories and hence lose their effectiveness when mixed types of road profiles are encountered that are difficult to classify. Thus a novel control algorithm is developed which is easy to implement online and more responsive to the varying road profiles that are encountered by the vehicle.
A numerical methods-based semi-active suspension control algorithm and a Model Predictive Control(MPC)-based semi-active suspension control algorithm are developed that can leverage the data from the upcoming road profile to increase the ride comfort of the vehicle. The numerical methods-based algorithm is developed for the sole purpose of determining the maximum possible ride comfort that can be achieved using semi-active dampers capable of altering their damping characteristics every 0.01 seconds. The MPC-based algorithm is a more realistic algorithm that can be implemented in real-time and achieves on average 70% of the ride comfort that the numerical methods-based algorithm can with minimal computational effort. / Master of Science / Semi-active suspensions help cars ride more smoothly and handle better on the road. However, they often react to bumps and potholes only after hitting them, which means there's room for improvement. By using information about the road ahead, these suspensions can adjust before reaching rough spots, making the ride even better.
To make this work, a new control system was developed. This system includes two parts. The first part uses detailed calculations to find the best possible comfort level, adjusting the suspension every 0.01 seconds. This method shows the highest comfort that can be achieved but is too complex for everyday use.
The second part uses a simpler method called Model Predictive Control (MPC). This part is practical for real-time driving and achieves about 70% of the best possible comfort. It doesn't need as much computing power and can quickly adapt to different road conditions, making it ideal for normal driving. This new system improves driving comfort and safety by making suspensions smarter and more efficient.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/119190 |
| Date | 30 May 2024 |
| Creators | Thamarai Kannan, Harish Kumar |
| Contributors | Mechanical Engineering, Ferris, John B., Warfford, Jeffrey Thomas, Taheri, Saied |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0018 seconds