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 (ISO 2006a, b) recommendation for goal definition. Secondly, studies have been categorized based on technical and methodological scope, and searched for coherent conclusions. Comprehensive goal formulation according to the ISO standard (ISO 2006a, b) is absent in most reviewed studies. Few give any account of the time scope, indicating the temporal validity of results and conclusions. Furthermore, most studies focus on today’s electric vehicle technology, which is under strong development. Consequently, there is a lack of future time perspective, e.g., to advances in material processing, manufacturing of parts, and changes in electricity production. Nevertheless, robust assessment conclusions may still be identified. Most obvious is that electricity production is the main cause of environmental impact for externally chargeable vehicles. If, and only if, the charging electricity has very low emissions of fossil carbon, electric vehicles can reach their full potential in mitigating global warming. Consequently, it is surprising that almost no studies make this stipulation a main conclusion and try to convey it as a clear message to relevant stakeholders. Also, obtaining resources can be observed as a key area for future research. In mining, leakage of toxic substances from mine tailings has been highlighted. Efficient recycling, which is often assumed in LCA studies of electrified vehicles, may reduce demand for virgin resources and production energy. However, its realization remains a future challenge. LCA studies with clearly stated purposes and time scope are key to stakeholder lessons and guidance. It is also necessary for quality assurance. LCA practitioners studying hybrid and electric vehicles are strongly recommended to provide comprehensive and clear goal and scope formulation in line with the ISO standard (ISO 2006a, b).

This study presents a review of how the end-of-life (EOL) stage is modelled in life cycle assessment (LCA) studies of lithium-ion batteries (LIBs). Twenty-five peer-reviewed journal and conference papers that consider the whole LIB life cycle and describe their EOL modelling approach sufficiently were analyzed. The studies were categorized based on two archetypal EOL modelling approaches in LCA: The cutoff (no material recovery, possibly secondary material input) and EOL recycling (material recovery, only primary material input) approaches. It was found that 19 of the studies followed the EOL recycling approach and 6 the cutoff approach. In addition, almost a third of the studies deviated from the expected setup of the two methods by including both material recovery and secondary material input. Such hybrid approaches may lead to double counting of recycling benefits by both including secondary input (as in the cutoff approach) and substituting primary materials (as in the EOL recycling approach). If the archetypal EOL modelling approaches are not followed, it is imperative that the modelling choices are well-documented and motivated to avoid double counting that leads to over- or underestimations of the environmental impacts of LIBs. Also, 21 studies model hydrometallurgical treatment, and 17 completely omit waste collection.

Batteries are enablers for reducing fossil‐fuel dependency and climate‐change impacts. In this study, a prospective life cycle assessment (LCA) of large‐scale production of two different sodium‐ion battery (SIB) cells is performed with a cradle‐to‐gate system boundary. The SIB cells modeled have Prussian white cathodes and hard carbon anodes based only on abundant elements and thus constitute potentially preferable options to current lithium‐ion battery (LIB) cells from a mineral resource scarcity point of view. The functional unit was 1 kWh theoretical electricity storage capacity, and the specific energy density of the cells was 160 Wh/kg. Data for the cathode active material come from a large‐scale facility under construction and data for the SIB cell production is based on a large‐scale LIB cell gigafactory. For other SIB cell materials, prospective inventory data was obtained from a generic eight‐step procedure developed, which can be used by other LCA practitioners. The results show that both SIB cells indeed have considerably lower mineral resource scarcity impacts than nickel‐manganese‐cobalt (NMC)‐type LIB cells in a cradle‐to‐gate perspective, while their global warming impacts are on par. Main recommendations to SIB manufacturers are to source fossil‐free electricity for cell production and use hard carbon anodes based on lignin instead of phenolic resin. Additionally, since none of the assessed electrolytes had clearly lower cradle‐to‐gate impacts than any other, more research into SIB electrolyte materials with low environmental and resource impacts should be prioritized. An improvement of the SIB cell production model would be to obtain large‐scale production data specific to SIB cells.

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.

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.