Climate change is a relevant topic of current time in both political and social discussions. Since the transport of people and goods causes a significant share of CO2 emissions, it is the goal of politics to reduce these emissions through regulations. One possibility is a technology change to electric vehicles, which, however, are still only sold in small numbers. One reason for this is the low vehicle range per battery charge when driving on the highway. To solve the latter problem, there are various approaches that aim to increase the efficiency of the vehicle. One possibility, which has not been investigated in detail so far, is the reduction of temperature-dependent losses in the electric motor and inverter via thermal conditioning of the components by the thermal system. This approach is investigated in this dissertation. After presenting the fundamentals of temperature-dependent loss mechanisms in the electric motor and inverter, the state of the art is introduced. Then, the thermal and electrical modeling of the inverter, the electric motor and the thermal system is explained. The model predictive controller which is used to reduce the losses is also presented. On the basis of different highway, rural road and city drives, the possible efficiency increase by exploiting the temperature dependencies is shown by simulation. Special attention is given to the improvement of the long-distance capability of electric vehicles. With the aim of better understanding the thermal influenceability of the losses, the individual loss components of the electric motor and inverter are analyzed. It is shown that on the highway, savings are mainly possible through reduced AC copper losses by means of a hot electric motor. Since the controller lets the system heat up, there is an efficiency disadvantage of the inverter. To reduce this disadvantage, bypasses around the components are investigated for thermal decoupling. While this provides little additional savings, it can reduce inverter aging by reducing the junction temperature. Finally, the influence of inaccurate prediction data on the efficiency is investigated. From the results, it is concluded that the controller is robust to inaccurate prediction data and can achieve high efficiency gains even with coarse knowledge of the driving profile.
Modellprädiktive Regelung temperaturabhängiger Verluste von elektrischen Antriebssträngen in transienten Fahrzyklen
Model predictive control of temperature-dependent losses of electric powertrains in transient driving cycles
01.01.2024
1 Online-Ressource : Illustrationen pages
Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2024; Aachen : RWTH Aachen University 1 Online-Ressource : Illustrationen (2024). = Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2024
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Elektronische Ressource
Deutsch
Hochschulschrift , temperaturabhängige Wirkungsgrade ; Elektromotor ; modellprädiktive Regelung ; Effizienzerhöhung ; Antriebsstrang ; Längsdynamik ; Hystereseverluste ; Wirbelstromverluste ; Kupferverluste ; Schaltverluste ; Durchlassverluste ; Elektromobilität ; Elektrofahrzeug ; prädiktive Daten ; temperature-dependent losses ; hysteresis losses ; copper losses ; conduction losses ; switching losses ; electric motor ; efficiency increase ; model predictive control ; powertrains ; longitudinal dynamics ; Eddy Current Losses ; electric vehicles ; electric mobility ; predictive data
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