A Transport Perspective on Designing European Battery Supply Chains: The PowerCo Case

This paper examines the process of designing a modern battery supply chain, emphasizing the complexity of establishing a supply chain with more than six components and 25 production steps. Focusing on PowerCo in Salzgitter, Germany, the study evaluates supply chain design from a transportation perspective, analyzing transport costs and emissions across six different scenarios. It explores how optimization strategies can minimize both costs and environmental impact, acknowledging the higher premiums associated with using European production. Additionally, the total transportation impact for cells supplied to Volkswagen‘s Wolfsburg plant from PowerCo Salzgitter and three other European manufacturers is assessed, highlighting the strategic advantage of PowerCo‘s plant location.

Keywords: Battery logistics; European Battery supply chain; Supply chain; Battery; Transport impact; Battery market; PowerCo.

1. Introduction

The demand for lithium-ion battery cells is increasing globally, with Europe experiencing particularly rapid growth. The discussion of supply chain security and independence remains prominent at all levels, from small industries to European policymakers. Although European cell manufacturing has expanded in recent years, these facilities have primarily been established by non-European companies. Prominent examples include LG, which operates the largest plant in Europe, others are CATL and SK, each managing two plants across the continent (Bockey and Heimes, 2026). European firms venturing into gigafactory-scale production have encountered mixed results, notably the bankruptcy of Swedish Northvolt in 2025 (Northvolt, 2025). Nonetheless, 2025 also marked positive developments for European battery manufacturers, exemplified by the opening of new production lines by French Verkor and German PowerCo, alongside existing operators like ACC, all of which aim to strengthen their presence in the battery industry (Automotive Cells Co, 2023; Groß, 2025; Verkor, 2025). The three have different origins but share similar public goals: low-emission European cells with secure manufacturing. Both ACC and PowerCo have founders connected to the automotive sector, with the goal of establishing “domestic” cell production. The key distinction is that ACC was formed by a consortium initially of Stellantis and TotalEnergies/Saft, later expanded to include Mercedes-Benz, whereas PowerCo was spun off from Volkswagen, primarily to supply cells for VW vehicles (Automotive Cells Co, 2022; Kilian et al., 2022). Since PowerCo is expanding its supply chain around a fully German-made cell production facility, analyzing the influence of various supply chain configurations on overall transport emissions and costs for the cells produced at the Salzgitter plant can provide insights into potential improvements to the supply chain.
This work will build on the authors‘ previously presented work on battery supply chain transport (Thomsen and Lux, 2025) by using a prismatic Lithium Nickel Manganese Cobalt Oxide 811 (NMC811) & graphite cell as a proxy for the top-tier unified cell using NMC chemistry, intended for production at the PowerCo plant (Groß, 2025). This cell raises three different aspects of interest when considering the impact of transport on the PowerCo supply chain.
(1) How do differently designed scenarios affect transport costs (€/kWh) and emissions (kg_eq-CO2/kWh) of PowerCo‘s cell manufacturing at its plant in Salzgitter, Germany?
(2) How does an increased number of European suppliers in the supply chain influence transport costs (€/kWh) and emissions (kg_eq-CO2/kWh) for PowerCo‘s Salzgitter plant?
(3) How does PowerCo compare to three European competitors as a cell supplier for VW, specifically from a transport perspective?
By examining these three aspects, we gain a clear understanding of whether the location of the PowerCo cell plant is strategic for its main customer, VW (Groß, 2025). It also explores how PowerCo might reduce transportation impacts in its supply chain through optimization and assesses how including European locations can further mitigate these impacts.

2. Methods

The methods and approach used in this work follow those published by the authors in their previous work (Thomsen & Lux 2025). Using the in-house developed multimodal point-to-point transport model, considering road, rail, and ocean-going transport, to determine the distance between factory locations in the data set. The distance is then converted to transport cost and emissions using material content, packaging and process efficiency, with emissions factors from The European Chemical Industry Council (Cerif) (McKinnon & Piecyk, 2021) and cost factors from Panteia (van der Meulen et al., 2023). The previous work focused on establishing a basis for analyzing the impact of transport in the battery supply chains. The findings showed a consistent, flexible, and independent approach to simulating transport and determining total supply chain transport cost and emissions. This work is in part based on the learnings from the first publication by extending. The scope of the original publication is extended by Increasing the number of scenarios considered, introducing new cell manufacturers and a new module manufacturer, improving material information, and focusing on a predominantly European supply chain. The PowerCo plant location, scenarios and outputs are shown in Figure 1 and described in the sections below.

Figure 1. The figure shows four elements. (Location) The locations of the PowerCo Salzgitter plant, Ionway Nysa plant and all European factories included in the model. (Scenarios) The six scenarios are presented with title, description and indicators for the cost, emission and China dependency. (Supply Chain information) The number of production steps and total number of factories. (Output values) The output values and their units.

2.1 Scenario

The dataset from the paper, From mine to manufacturer: Assessing transport impacts in the battery supply chain, (Thomsen & Lux 2025) was used to broaden the analysis to six scenarios. These include (a) the state-of-the-art (SOA), (b) the lowest transport emissions scenario, and (d) the lowest transport costs scenario. The scenarios represent the material flows within the SOA and the optimal setups for each parameter. Using this data, a balanced scenario (c) was constructed by selecting the nearest supply chain to the intersection of minimum emissions and cost to approximate a supply chain that minimizes combined emissions and costs. A scenario (f) with the fewest locations within China was developed to depict a China-limited supply chain. The China-limited supply chain was then adapted to a European cathode active material supply chain (EU CAM) built around the joint venture IonWay, formed by PowerCo and Umicore, for the production of cathode active materials in Poland (e) (Ernst and Scheers, 2023; IONWAY, 2023). The scenarios were chosen to illustrate non-idealized supply chains and to evaluate the impact of a potential exclusion of China on transportation impacts.

2.2 Cell manufacturing comparison

To compare European cell manufacturers delivering to the Volkswagen plant in Wolfsburg, the SOA supply chain for each manufacturer was designed, and the distance between the cell manufacturer and the automotive plant was determined using the simulator. These distances were then converted to cost and emissions. The plants chosen were the Samsung SDI battery cell plant in Göd, Hungary, the LG plant in Wrocław, Poland, the Verkor battery cell plant in Dunkirk, France, and the Volkswagen Automotive plant in Wolfsburg, Germany. The cell manufacturers were selected based on size and location, with LG representing the largest plant in Europe, Samsung SDI as a proxy for a multitude of the plants in Hungary, and Verkor representing a batterycentric region in France.

3. Results

The results for the six scenarios are shown in two parts: Figure 2A displays the greenhouse gas (GHG) emissions in kg_eq-CO2/kWh, while Figure 2B shows the associated transport costs in €/kWh. The data is divided into eight categories: Cathode Active Material, Natural Graphite, Synthetic Graphite, Aluminum Casing, Aluminum Foil, Copper Foil, Solvent, and Separator. The total transport emissions in the SOA scenario are calculated to be 4.15 kg_eq-CO2/kWh, with a transport cost of 3.96 €/kWh. The first important finding is that all modified scenarios have both lower cost and lower emissions than the SOA scenario. This indicates that, from the SOA scenario, there is a high potential for optimization through even small changes to the supply chain, including bringing parts of the supply chain to or near Europe. After adjusting the full-cell cost and emissions reported by Gutsch and Leker (Gutsch & Leker, 2024) to the cell capacity used in this study, transport was found to account for 5.0% of total cell emissions and 3.2% of total cell cost. By design, the largest savings are observed for the optimized scenarios, with the cost-optimized scenario showing a potential 61% cost reduction and the emission-optimized case showing a potential 41% emission reduction. The balanced scenario shows a 59% potential cost reduction and a 38% potential emission reduction. The balanced scenario proves to be a good compromise between the best emission and cost scenarios. Especially for emissions, the balanced scenario performs 10 percentage points better than the cost-optimized scenario. On the material level aspect, in all scenarios, transport of the separator accounts for the smallest contribution, while the main contributor varies depending on the scenario and key performance indicator. In the SOA case, the copper supply chain has the highest transport costs and emissions, but also offers the greatest potential for savings, with potentially 86% reduction in emissions and 89% reduction in costs. When comparing the costs, emissions, and balanced scenarios, three of the eight categories show no significant variation: Aluminum Foil, Casing, and Natural Graphite. Small variations are seen in the cathode active material, Copper foil, separator, and solvent. The most significant variation occurs in emissions for Synthetic Graphite, which nearly doubles from the emission to the cost scenario. An interesting aspect is the comparison between the two scenarios constructed to target a Chinese-limited supply chain. These scenarios propose that PowerCo would aim to limit the use of Chinese materials in the cell; consequently, the resulting scenarios involve only three manufacturing steps in China, all related to graphite production. These two scenarios exhibit the highest overall transport costs and emissions for the modified scenarios, primarily due to the cathode active material and aluminum casing. Here, the EU CAM scenario incurs the highest overall transport cost, with CAM transport costs in this scenario being double that of the cost-optimized scenario and 80% of the SOA scenario. Despite this, the CAM supply chain records the lowest emissions among all scenarios, suggesting that a European supply chain for the EU CAM scenario results in a transport cost premium, but emission savings. Conversely, the Chinalimited scenario has the highest total transport and CAM-specific emissions, although its transport costs are lower than those of the EU CAM scenario.

Figure 2: This figure shows the emissions (A) and transport costs (B) for the six scenarios designed in this study. The transport costs and emissions are shown for each of the eight components of the cell. At the top of each bar is the total transport cost or emission reported and the reduction in percentage compared to the state of art (SOA) scenario.

4. Discussion

The findings highlight the impact of transport costs and emissions throughout the supply chain and indicate that, while reductions are achievable, both the China Limited and the EU CAM scenarios deviate notably from the optimized scenarios. The following aspects require further discussion. The first concerns how PowerCo‘s transport costs and emissions compare with those of other European cell manufacturers for cells delivered to the VW plant. The second concerns how reducing reliance on Chinese materials and increasing local sourcing may raise transport costs and emissions, but could provide greater supply chain security.

4.1 PowerCo as a cell Supplier for VW

VW created PowerCo as a key component supplier to their headquarters and production site in Wolfsburg, Germany. The chosen location for the first PowerCo plant in Salzgitter, Germany, took this into account. To evaluate the location choice, a comparison of total supply chain transport costs for cells from PowerCo and three other European cell manufacturers was conducted, with the cells arriving at the VW plant in Wolfsburg. The selected manufacturers are LG in Wrocław, Poland; Verkor in Dunkirk, France; and Samsung SDI in Göd, Hungary. The results for the SOA scenario are shown in Figure 3. The results clearly indicate that for two of the three other cell manufacturers, the total supply chain transport cost is higher than for the PowerCo plant, ranging from a premium of 0.25€/kWh for the Verkor plant to 0.68€/kWh for the Samsung SDI. This suggests that, from a transportation cost perspective, the PowerCo plant‘s location in Salzgitter is advantageous, and reduced supply chain transport costs enhance PowerCo‘s competitiveness with other European cell manufacturers.

Figure 3. The map shows the location of the Volkswagen plant in Wolfsburg (Car) and the nearby PowerCo plant (P), as well as the location of the three alternative cell plants chosen by Verkor (A), LG (B), and Samsung (C). The table shows the total supply chain distance, costs, and emissions for cells transported to the Volkswagen plant.

4.2 The implications of increased European material sourcing

Production locations are linked directly to potential product cost, tariffs, and procurement times for input and output materials, connecting local content and supply chain security. The EU CAM and China limited scenarios show how increased European content affects transport costs and emissions. Table 1 lists the 11 production steps that occur in Europe at least once across the six scenarios, based on the database used in this study. European factories for alumina, aluminum, and copper are readily available. Nevertheless, the database includes only the top 3 global producers for each category, and European locations are not among the top producers of alumina and aluminum; an alternative would be to use recycled European copper in the manufacturing process, which has already been reported in industry (Volta Energy 2021). As Europe is not currently the leading producer at any stage in the battery supply chain, the SOA scenario includes no European production. This supply chain not only illustrates the most likely material flow but also the most far-east Asia dependent supply chain analyzed in this study. Therefore, any inclusion of European manufacturers would be a deviation from the SOA supply chain. In the optimized scenarios, a clear distinction appears between the cost- and emission-optimized scenarios. The cost scenarios include some of the NMC upstream precursor-refining stages in Europe. Meanwhile, the emission scenario includes manufacturing steps for copper foil, electrolyte, and separator occurring in Europe. This information can be used to compare the balanced scenario, in which only one production step is in Europe: separator manufacturing. This scenario balances cost and emissions equally to identify the best average outcome; under these conditions, European steps are generally not favored. If the decision was made to use all European production sites from the optimized scenarios for the balanced scenario, it would yield greater cost savings but higher emissions. With transport cost at 1.6€/kWh and transport emissions at 2.84kg_eq-CO2/kWh. Targeting a European-heavy, China-limited supply chain in the EU CAM and China-limited scenarios, higher costs and emissions were observed in the results. The higher cost is associated with more production sites in Europe: the China-limited has 8, whereas the EU CAM has 11. This equals 40% of the overall production locations located in Europe, compared with zero in the SOA scenario, the increase in transport costs due to the higher number of European sites are 0.7€/kWh, or about 43% higher than in the cost-optimized scenario.

Table 1: Heat map indicating which of the 11 European production steps are included in each scenario. Green is included, red is not included.

5. Perspective

Industrial supply chain information is hard to obtain outside joint-venture announcements, such as IONWAY. Because this information is often considered proprietary, Volkswagen publishes an annual Responsible raw materials report, in which they comment on raw material sourcing and refinement (Volkswagen AG, 2026). This report is at the group level and therefore covers more raw materials and other potential cell producers for Volkswagen; however, it remains a good indicator of the PowerCo supply chain. Three points from this report are of interest for this publication. There is a high degree of similarity between the global leading mining countries in the report and those in this publication, and the three leading countries often appear as sources. PowerCo sources material from multiple countries simultaneously, rather than from a single origin as simulated in this study. Importantly, the report states that mapping battery materials across the full supply chain is difficult, but that “refining and processing remain highly concentrated in China.” (Volkswagen AG, 2026). This indicates that PowerCo, as a company, is close to the mid- and downstream design of the SOA scenario, deviating from SOA by sourcing raw materials from multiple locations around the globe. This work demonstrates the potential savings achievable through supply chain optimization for a single company at a specific production step. However, the lessons drawn from transport are relevant beyond this particular case. Including transport in supply chain analysis provides a broader basis for evaluating location suitability in relation to both suppliers and customers. Because transportation costs often represent an additional cost borne by the buyer, a stronger understanding of supply chain transport costs can improve competitiveness in tight markets by supporting more effective supply chain and transport design, as illustrated here in the case of PowerCo and Volkswagen.

6. Conclusion

Six supply chain scenarios for battery cell manufacturing at the PowerCo plant in Salzgitter, Germany, were evaluated and analyzed. A cost-optimized and an emission-optimized scenario were used as theoretical bookends to approximate a balanced scenario. Additionally, the reduction in dependence on China was assessed, including the PowerCo special case involving a joint venture in Poland for the supply of cathode active material. The optimized scenarios indicated potential savings of over 40% in transport emissions and 60% in transport costs, however these have very limited European contributions. In the EU CAM and China-limited scenarios, most categories exhibited lower costs and emissions than in the SOA scenarios. Notable values include the cost of the CAM supply chain in the CAM EU scenario, which shows only a 20% reduction compared to the SOA scenario and is twice that of the optimized scenarios. Regarding emissions, in both scenarios, the transportation of synthetic graphite is nearly twice that of the SOA and emission-optimized scenarios. Both scenarios involved numerous European locations, but the expanded European footprint increased transport costs and emissions. Finally, the location of the PowerCo plant as a supplier for Volkswagen was evaluated by comparing it with three other European cell plants. The analysis showed that PowerCo has a 25-cent-per-kWh transportation cost advantage over the second-best producer in a fullsupply-chain transport analysis. Overall, this study demonstrates that PowerCo, via its main offtake agreement with Volkswagen, was able to establish a factory with near-optimal transport costs and emissions for cell delivery. The research highlighted how this advantage could be enhanced through supply chain optimization and expanding the number of European manufacturers. Nevertheless, in some parts of the supply chain, utilizing a European supply chain would increase transport costs, which would have to be offset by lower production costs or balanced with greater supply chain resilience.

Statement of AI Usage

ChatGPT, version 5.4, extended thinking has been used to improve content quality, and Grammarly, with the Grammarly AI writing assistant, has been used to improve writing. After employing these tools, we thoroughly reviewed and edited the content as necessary, assuming full responsibility for the final publication.

Acknowledgement

The authors would like to acknowledge that the map data used for this work are copyrighted by OpenStreetMap contributors and available from https:// www.openstreetmap.org. Calculations (or parts of them) for this publication were performed on the HPC cluster PALMA II of the University of Münster, subsidised by the DFG (INST 211/667-1).

CRediT authorship contribution statement

Jesper Frost Thomsen: Writing – original draft, Visualization, Validation, Resources, Methodology, Investigation, Conceptualization.
Simon Lux: Writing – original draft, Supervision, Conceptualization.

Funding sources

The authors thank the Ministry for Culture and Science of North Rhine-Westphalia (Germany) for funding this work within the International Graduate School for Battery Chemistry, Characterization, Analysis, Recycling, and Application (BACCARA). The funder had no influence or impact on the work carried out in this study.

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