Real-time route identification, mass estimation and velocity profile optimisation

This dataset contains the recorded test data and executable programme files to perform route identification, mass estimation and velocity profile optimisation in real-time. The software used includes Excel, Octave 4.1, Matlab 2021b and Simulink. All of these form part of a PhD thesis, each set contributing to a section of the work in isolation. In the folder named, Phase 1_underground navigation, there is all the test data for road tests, where magnetic heading, barometric altitude, driving torque etc. is stored. These are used to identify routes that were travelled based on patterns in heading and change in altitude. It was found that patterns in heading and barometric altitude can be effectively used to identify a known route by.

In the folder named, Phase 2 Mass estimation, the data available for driving torque, speed, incline etc., which is used to obtain an estimate for a vehicle's mass in real-time. By applying newton's second law for a vehicle on an incline, and rearranging the equations to solve for the mass, M, it is possible to obtain a real-time estimate for the vehicle's mass. In the folder named, Phase 3 optimisation, the codes required to run an optimisation of a velocity profile for a vehicle on a known route is presented. The initial guess plays a significant role in any optimisation problem, and in this study a method was developed that makes use of an inverted version of the route topographic profile as an initial guess to the optimisation problem. This was proven to be very effective, and also proved to be capable of being used as an estimate to the optimal problem, at a significantly reduced simulation time (20 seconds, vs 3 hours). This method was converted to a lookup table which is able to solve in milliseconds, allowing real-time application.