Purpose A scalable life cycle inventory (LCI) model, which provides mass composition and manufacturing data for a power electronic inverter unit intended for controlling electric vehicle propulsion motors, was developed. The purpose is to fill existing data gaps for life cycle assessment (LCA) of electric vehicles. The model comprises new and easy-to-use data with sufficient level of detail to enable proper component scaling and more in-depth analysis of inverter units. It represents a stand-alone three-phase inverter with insulated gate bipolar transistors (IGBTs), typical in electric vehicles. This article (part I) explains the modeling of the inverter design including the principles for scaling, exemplifies results, and evaluates the models' mass estimations. Methods Data for the design of power electronic inverter units was compiled from material content declarations, textbooks, technology benchmarking literature, experts in industry, and product descriptions. Detailed technical documentation for two electrically and electronically complete inverter units were used as a baseline and were supplemented with data for casings, connectors, and bus bars suitable for automotive applications. Data, theory, and design rules were combined to establish a complete model, which calculates the mass of all subparts from an input of nominal power and DC system voltage. The validity of the mass estimates was evaluated through comparison with data for real automotive inverter units. Results and discussion The results of the LCI model exemplifies how the composition of the inverter unit varies within the model range of 20-200 kW and 250-700 V, from small passenger car applications up to distribution trucks or city buses. The models' mass estimations deviate up to 14% from the specified mass for ten examples of real inverter units. Despite the many challenges of creating a generic model of a vehicle powertrain part, including expected variability in design, all results of the model validation fall within the targeted goal for accuracy. Preamble This is the first article in a series of two presenting a new scalable life cycle inventory (LCI) data model of a power electronic inverter unit for control of electrical machines in vehicles, available to download. In part I, it is described how the LCI model was established, how it is structured, and the type of results it provides, including a validating comparison with real-world inverter units. It also covers design data and the principles for scaling of the main active parts-the power module and the DC link capacitor. Part II presents how new production datasets were compiled from literature and factory data to cover the manufacturing chain of all parts, including the power module fabrication, mounting of printed circuit boards, and the complete assembly. Part II also explains the data collection methods, system boundaries, and how to link the gate-to-gate inventory to the Ecoinvent database in order to establish a complete cradle-to-gate LCI.
Purpose A scalable life cycle inventory (LCI) model of a permanent magnet electrical machine, containing both design and production data, has been established. The purpose is to contribute with new and easy-to-use data for LCA of electric vehicles by providing a scalable mass estimation and manufacturing inventory for a typical electrical automotive traction machine. The aim of this article (part I of two publications) is to present the machine design, the model structure, and an evaluation of the models' mass estimations. Methods Data for design and production of electrical machines has been compiled from books, scientific papers, benchmarking literature, expert interviews, various specifications, factory records, and a factory site visit. For the design part, one small and one large reference machine were constructed in a software tool, which linked the machines' maximum ability to deliver torque to the mass of its electromagnetically active parts. Additional data for remaining parts was then gathered separately to make the design complete. The two datasets were combined into one model, which calculates the mass of all motor subparts from an input of maximum power and torque. The range of the model is 20-200 kW and 48-477 Nm. The validity of the model was evaluated through comparison with seven permanent magnet electrical traction machines from established brands. Results and discussion The LCI model was successfully implemented to calculate the mass content of 20 different materials in the motor. The models' mass estimations deviate up to 21% from the examples of real motors, which still falls within expectations for a good result, considering a noticeable variability in design, even for the same machine type and similar requirements. The model results form a rough and reasonable median in comparison to the pattern created by all data points. Also, the reference motors were assessed for performance, showing that the electromagnetic efficiency reaches 96-97%. Conclusions The LCI model relies on thorough design data collection and fundamental electromagnetic theory. The selected design has a high efficiency, and the motor is suitable for electric propulsion of vehicles. Furthermore, the LCI model generates representative mass estimations when compared with recently published data for electrical traction machines. Hence, for permanent magnet-type machines, the LCI model may be used as a generic component estimation for LCA of electric vehicles, when specific data is lacking.Keywords Electric . Electrical . Inventory . IPM . IPMSM . Life cycle assessment . Machine . Magnet . Mass . Material Preamble This series of two articles presents a new scalable life cycle inventory (LCI) data model of an electrical automotive traction machine, available to download from the CPM database of the Swedish Life Cycle Center. Part I describes how the LCI model was established and the type of results it provides, including the underlying permanent magnet synchronous machine (PMSM) design and the structure of the LCI data m...
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