Vehicle Dynamics Analysis to Optimise a Formula Student Car Setup

This dissertation aim is to perform vehicle dynamics analysis to optimise a Formula Student car behaviour, preparing a final setup to reduce 2018 FSUK autocross laptime of at least 2%. The main objectives are: - Understand OBR18 and OBR19 cornering behaviour. - Obtain and validate with previous results a baseline quasi-static and transient laptime simulation for OBR18. - Optimise OBR19 setup to achieve the aim laptime. - Validate the optimised model with on-track tests of OBR19 best configuration. There are three main key points for this project success: - Data collection: inputs accuracy is important to well model and simulate the complete cars. - Validation (within 10% of error): it is needed between different models before optimisation phase would begin. Overall validated models means that optimisation can be expected to work properly when implemented in the real vehicle. - Optimisation: this phase allows the aim to be achieved, preparing the best setup possible for FSUK 2019. Analytical and numerical models are used to understand both vehicles cornering behaviour. Comparing them, it is possible to achieve a validation. Laptime simulations implementation (quasi-static and transient) is used to model OBR18 in FSUK autocross racetrack, validating FSUK 2018 laptime. Starting from this validated model, OBR19 is modelled in the transient simulator allowing the optimisation phase begin. Achieving the aim laptime, on-track tests validation has been performed for the best virtual setup. Important findings such as the cornering response validation between derivatives and bicycle model are presented. Negligible tolerance error achieved means good vehicles design, representing an excellent starting point for OBR19 performance optimisation phase. Setup optimisation is performed considering the most important and quickest parameters to setup with on-track tight deadlines. Sensitivity studies for those parameters are used to setup OBR19 for FSUK 2019 autocross, knowing the potential performance optimisation from laptime simulations and on-track tests. Important limitations about the absence of a driver models are explained discussing the results. It is also demonstrated how an accurate vehicle dynamics correlation between mathematical models and real world has been essential to led Oxford Brookes Racing to the FSUK 2019 2nd place overall. Relevant future work are presented in the conclusion