The development of a numerical temperature algorithm to predict the indoor temperature of an electric vehicle's cabin space
  The demand for the electric vehicle has increased as the automobile industry, governments and scientific community acknowledge its potential to help mitigate greenhouse gasses from the atmosphere. However barriers exist that hinder driver uptake and still fossil fuelled vehicles dominate the market. ‘Range anxiety’ is the primary concern with a battery powered vehicle. With the conventional internal combustion engine ‘waste heat’ from the engine is used to heat the vehicle for free, however, this energy cannot be harnessed in electric vehicles as little heat is emitted from the battery. With varying ambient temperatures there is a high demand for heating and cooling requirements on the vehicle’s primary battery. This research is developing an algorithm that can predict indoor cabin temperature. With this algorithm occupants can predict how much energy will be required by the built-in climate control system to cool or heat the vehicle’s cabin space. Additionally, this research analysis the benefits of introducing an auxiliary heating and cooling system to the vehicle independent to the primary lithium-ion battery. The research includes a feasibility study on the integration of solar panels on the roof and bonnet of the vehicle to assist in recharging of the auxiliary heating and cooling system.

  • Dates:

    2014 to 2018

  • Qualification:

    Doctorate (PhD)

Project Team

Research Areas