The purpose of this review article is to investigate the usefulness of different types of life cycle assessment (LCA) studies of electrified vehicles to provide robust and relevant stakeholder information. It presents synthesized conclusions based on 79 papers. Another objective is to search for explanations to divergence and “complexity” of results found by other overviewing papers in the research field, and to compile methodological learnings. The hypothesis was that such divergence could be explained by differences in goal and scope definitions of the reviewed LCA studies. 

The review has set special attention to the goal and scope formulation of all included studies. First, completeness and clarity have been assessed in view of the ISO standard’s recommendation for goal definition. Secondly, studies have been categorized based on technical and methodological scope, and searched for coherent conclusions.

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 life cycle assessment (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 II of two publications) is to present the manufacturing data with associated collection procedures, from material constituents to complete motor. Another objective is to explain the gate-to-gate system boundaries and the principles for linking the LCI model upstream, to database data, in order to create a full cradle-to-gate dataset. 

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 manufacturing part, new primary data was collected directly from industry, with a motor factory and a steel mill in Sweden as main contributors, and from technical literature. Other LCA publications were used, if presented in sufficient detail to be disaggregated and revised, to match the gaps of the model. The data represents the current level of technology and targets high-volume manufacturing to the largest extent possible. Also, flows crossing the system boundary have a recommended link to Ecoinvent data, or a request for an attentive selection of input data, depending on the user’s object of study. A distinction was made between the regular and an extended system boundary, wherein the processing of some smaller subparts was accounted for through proposals of ready-made Ecoinvent activities for production efforts. 

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. 

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. 

Ongoing development of electrified road vehicles entails a risk of conflict between resource issues and the reduction of greenhouse gas emissions. In this study, the environmental impact of the core design and magnet material for three electric vehicle traction motors was explored with life cycle assessment (LCA): two permanent magnet synchronous machines with neodymium-dysprosium-iron-boron or samarium-cobalt magnets, and a permanent magnet-assisted synchronous reluctance machine (PM-assisted SynRM) with strontium-ferrite magnets. These combinations of motor types and magnets, although highly relevant for vehicles, are new subjects for LCA. The study included substantial data compilation, machine design and drive-cycle calculations. All motors handle equal take-off, top speed, and driving conditions. The production (except of magnets) and use phases are modeled for two countries – Sweden and the USA – to exemplify the effects of different electricity supply. Impacts on climate change and human toxicity were found to be most important. Complete manufacturing range within 1.7–2.0 g CO2-eq./km for all options. The PM-assisted SynRM has the highest efficiency and lowest emissions of CO2. Copper production is significant for toxicity impacts and effects on human health, with problematic emissions from mining. Resource depletion results are divergent depending on evaluation method, but a sensitivity analysis proved other results to be robust. Key motor design targets are identified: high energy efficiency, slender housings, compact end-windings, segmented laminates to reduce production scrap, and easy disassembly. 

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. 

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.

A scalable life cycle inventory (LCI) model, which provides mass composition and gate-to-gate 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 in-depth analysis of inverter units. The aim of this article (part II) is to describe the modeling of all production steps and present new datasets. Another objective is to explain the strategies for data collection, system boundaries, and how unit process datasets were made to interact properly with the scalable design model (part I). 

Data for the manufacturing of the inverter unit was collected from a variety of literature, technical specifications, factory data, site visits, and expert interviews. The model represents current levels of technology and modern industrial scale production. Industry data dates back to 2012. Some older literature is referred to, but only if it was found to remain relevant. Upstream, new data has been gathered to the point where the Ecoinvent database can be used to model a full cradle-to-gate inventory. To make the LCI model easy to use, each flow crossing the system boundary is reported with a recommended linked flow to this database.