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Electric Vehicle Inverter Electro-Thermal Models Oriented to Simulation Speed and Accuracy Multi-Objective Targets

With the increasing demand for electric vehicles, the requirements of the market are changing ever faster. Therefore, there is a need to improve the electric car’s design time, where simulations could be an appropriate tool for this task. In this paper, the modeling and simulation of an inverter for an electric vehicle are presented. Four different modeling approaches are proposed, depending on the required simulation speed and accuracy in each case. In addition, these models can provide up to 150 different electric modeling and three different thermal modeling variants. Therefore, in total, there were 450 different electrical and thermal variants. These variants are easily selectable and usable and offer different options to calculate the electrical parameters of the inverter. Finally, the speed and accuracy of the different models were compared and the obtained results presented.
- Mondragon University Spain
- Vrije Universiteit Brussel Belgium
- Mondragon University Spain
Technology, T, electric vehicle, electric vehicle; hybrid electric vehicle; inverter modeling; thermal modeling; power electronics; modulation techniques; semiconductor power losses, thermal modeling, modulation techniques, power electronics, inverter modeling, hybrid electric vehicle, semiconductor power losses
Technology, T, electric vehicle, electric vehicle; hybrid electric vehicle; inverter modeling; thermal modeling; power electronics; modulation techniques; semiconductor power losses, thermal modeling, modulation techniques, power electronics, inverter modeling, hybrid electric vehicle, semiconductor power losses
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).15 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
