Electromagnetically Interconnected Suspension for Electrified Vehicles . This project aims to develop an innovative, electromagnetically interconnected suspension system to enhance vehicle ride comfort, stability and handling dynamics, and thus safety of electrified vehicles. Specifically, the project integrates a set of novel electromagnetic shock absorbers to form an effective electrical network so as to realise an electromagnetically interconnected suspension system. Advanced integrated con ....Electromagnetically Interconnected Suspension for Electrified Vehicles . This project aims to develop an innovative, electromagnetically interconnected suspension system to enhance vehicle ride comfort, stability and handling dynamics, and thus safety of electrified vehicles. Specifically, the project integrates a set of novel electromagnetic shock absorbers to form an effective electrical network so as to realise an electromagnetically interconnected suspension system. Advanced integrated control techniques can then be applied to improve vehicle performance and dynamics in three planes. The project will assist the rapid development of transportation electrification. The outcomes from this project will lead to tangible improvements in vehicle comfort and safety.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101676
Funder
Australian Research Council
Funding Amount
$435,690.00
Summary
Machine learning-based design of triply periodic minimal surface structures. This project aims to develop a new approach to design of new lightweight, crashworthy and manufacturable structures by taking advantage of the latest technologies in computational optimisation, artificial intelligence and additive manufacturing. The study intends to develop a new machine learning-based multiscale design framework to seek optimal triply periodic minimal surface structures, considering fabrication-induced ....Machine learning-based design of triply periodic minimal surface structures. This project aims to develop a new approach to design of new lightweight, crashworthy and manufacturable structures by taking advantage of the latest technologies in computational optimisation, artificial intelligence and additive manufacturing. The study intends to develop a new machine learning-based multiscale design framework to seek optimal triply periodic minimal surface structures, considering fabrication-induced defects and uncertainty. The expected outcome of this project is new methodologies for generating eco-friendly structures with robust mechanical properties in crashing applications. This should provide significant benefits to transport industries by enhancing structural safety and energy saving for next generation vehicles.Read moreRead less