This study assesses the potential for decarbonizing EU road transport through several pathways, focusing on the feasibility of achieving impact by 2035. Through comprehensive literature review, we compare the distance-levelized cost, lifecycle GHG emissions, and scalability of combustion engine vehicles (three fuels), battery-electric vehicles (BEVs, three charging methods), and hydrogen fuel cell vehicles. We consider projected transport growth and the current age composition and use of vehicles in Europe, segmented into four regions. Biofuels, hydrogen, and e-fuels are not found to have potential to significantly contribute to further GHG emissions before 2035 due to scalability and technological limitations. BEVs emerge as the only viable strategy for achieving zero tailpipe emissions at scale, with effective lifecycle GHG reductions constrained by the rate of decarbonization of steel production, battery production and EU electricity production. By 2035, embodied battery emissions are expected to be the dominant source of lifecycle emissions from electric vehicles. The environmental benefits of a BEV transition are primarily limited by the rate at which the vehicle stock can be electrified, with new electric vehicle sales contributing primarily to decarbonization in Northen and Western Europe. Combining the expected buildout of static charging infrastructure with a proposed pan-European Electric Road System (ERS) network is found to greatly accelerate the transition to electrified road transport, including in otherwise late-to-decarbonize segments, by removing cost, weight, and supply barriers to retrofitting older combustion engine cars with new electric powertrains. Other effects of an ERS network are found to be substantially reduced embodied emissions from BEV production, resulting from reduced battery capacity per vehicle, and reduced levelized freight costs. However, possibly insurmountable political and bureaucratic barriers must be overcome ERS to play any meaningful part in decarbonization of road transport within the coming decade. If the barriers can be overcome, the economic and ecological rewards are substantial. Despite identifying pathways for substantial emissions reductions, the study does not identify any technical pathway through which the EU road transport sector will not greatly exceed its fair share of global GHG emissions. In addition, our review of strategies to achieve modal shift and road transport demand reductions also fails to find indications that interventions in these areas will have GHG reduction effects of desired magnitude within the required timeframe, unless costs of vehicle ownership and use are raised substantially. Further policy research is urgently needed to find repeatable and socially just interventions through which total transport work, the size of the vehicle stock and embodied GHG emissions per vehicle can be reduced substantially across the entire EU before 2035.

This report presents an analysis to forecast the utilization of a future electric road system (ERS) network in Sweden. The analysis, limited to ERS use by heavy trucks, focuses on how ERS utilization is expected to evolve under different network scopes and levels of pricing. In addition, the socio-economic impact of adding ERS to the Swedish charging mix is estimated, and sensitivity analysis is performed with regards to the availability of infrastructure for static charging and national policies about biofuel use.

The questions are answered through comparative simulations in MOSTACHI, a tool developed to study spatio-temporal system dynamics during transport electrification, with parameter assumptions aligned with the Swedish Transport Administration’s guidelines (ASEK8). The analysis covers ERS networks spanning from 1000 to 3000 km and outcomes are compared across a range of indicators, including ERS utilization, system costs, transport electrification, CO2 emissions, and demand for energy, biofuels and batteries.

Simulations suggest that economic-environmental benefits of a Swedish ERS network would be maximized when the dynamic charging fee is set low enough that 80-90% of within-network traffic would be given economic incentives to charge dynamically. With a higher fee differentiated by willingness to pay (WTP), and 70-80% utilization, the full investment cost could likely be recouped within 25 years. Viable pricing is approximately in the span between that of night-time depot charging and day-time public fast-charging. WTP for all types of charging declines over time. Simulated WTP for dynamic charging is observed to be greater along the E4 than on the Swedish west coast.

A 1500 km ERS network operational from 2035 is forecast to raise the electrified share of road freight within the network from 50% to 90% and reduce total remaining national ICET traffic by one third (e.g., 40% to 60%). The effect size at national scale is determined by the scope of the ERS network, with larger networks achieving greater impact. ERS impact on traffic outside the network is minor in the simulations. Rapid ubiquitous buildout of overnight charging for trucks is recommended regardless of and in addition to ERS investments.

The opportunity cost of not investing in ERS in Sweden is estimated at over four billion euro until 2050, or 300 million euro per year of delay. These opportunity cost estimates assume very cheap batteries, expensive ERS and quick expansion of static charging. Under assumed future EU biofuel policy, ERS is forecast to reduce cumulative Swedish CO2 emissions from heavy trucks until 2050 by approximately 8 Mt, with an emissions opportunity cost of approximately 300 kt per year of delay. If Sweden is on a path to electrify less than 50% of road freight by 2035, opportunity cost estimates increase.

Data have been published stating that of all heavy trucks (>16 ton) that drive at least 5 days per year on the main Swedish road network (Malmö-Göteborg-Stockholm), only 15% drive more than 50% of their annual mileage on this road network . Intuitively, this gives the impression that charging infrastructure placed on the main road network cannot contribute greatly to electrification of heavy trucks. Meanwhile, route-based simulation of charging preferences on the Swedish road network has concluded that if Electric Road Systems (ERS) infrastructure is deployed on the main Swedish road network, >95% of heavy traffic on this road network would have sufficient financial incentive to becomes users of the ERS charging infrastructure.

Assessment of the future energy and power demand for charging of road traffic, per Swedish county, municipality and type of charging infrastructure The report forecasts future needs for electrical energy and power for charging electric vehicles throughout Sweden, with a particular focus on Västra Götaland. Annual energy demand and peak loads are forecast per Swedish county and municipality. Load curves divided into different categories of charging infrastructure are presented for scenarios with and without load balancing from evening to night, as well as where a share of the energy for road transport is transferred via hydrogen or electric roads. The uncertainty in the forecasts is substantial around 2035, due to uncertainty about how fast electrification of road traffic will proceed. Factors affecting the rate of electrification include taxes and subsidies that affect the cost difference between owning electric vehicles and internal combustion engine vehicles, electricity market price stability, crude oil prices and interest rates. The rate of electrification is also strongly influenced by the rate of expansion and pricing of charging infrastructure, where permits for new grid connections are a bottleneck for expansion. The report emphasizes the importance of achieving load balancing that redistributes vehicle charging from late afternoons to late evenings and nights, particularly within larger residential areas. Solving this challenge has a higher priority for the successful electrification of road transport than getting public fast charging stations in place, as charging at homes and truck depots form the backbone of an electrified road transport system. Challenges and opportunities with Vehicle-to-Grid (V2G) technology are discussed. The report also highlights the uncertainty surrounding the future use of driverless vehicles and their potential impact on charging needs and traffic patterns. The forecasts indicate that the total electricity demand for road transport will be slightly lower in winter than in summer, due to reduced traffic work and despite increased energy consumption at low temperatures. Electric roads would only increase energy demand if contributing to a faster rate of electrification, while large-scale use of fuel cell trucks and locally produced hydrogen would increase energy demand in the long term by roughly 10% and in the short term more, if only replacing combustion engine vehicles. Large-scale use of synthetic gasoline and diesel produced from green hydrogen is considered unlikely, but would greatly increase energy demand as long as internal combustion engine vehicles are still in use.

Rapporten prognostiserar framtida behov av elektrisk energi och effekt för laddning av elektriska vägfordon i hela Sverige, med särskilt fokus på Västra Götaland. Årligt energibehov och topplast prognostiseras per län och kommun. Lastkurvor uppdelade på olika kategorier laddinfrastruktur presenteras för scenarier med och utan lastbalansering från kvällar till nätter, samt där en betydande andel av energin till vägtransporterna överförs via vätgas eller elvägar. Osäkerheten i prognoserna är stor kring 2035, på grund av osäkerhet kring hur snabbt elektrifieringen kommer att gå. Faktorer som påverkar elektrifieringstakten inkluderar skatter och subventioner som påverkar det relativa kostnadsläget mellan elfordon och förbränningsmotorfordon, elmarknadens prisstabilitet, råoljepriser och räntor. Elektrifieringstakten påverkas även starkt av utbyggnadstakt och prissättning av laddinfrastruktur, där tillstånd för nya nätanslutningar är en flaskhals för utbyggnad. Rapporten betonar vikten av att få till lastbalansering som omfördelar fordonsladdning från sena eftermiddagar till sena kvällar och nätter, särskilt inom större bostadsområden. Att lösa denna utmaning har högre prioritet för en framgångsrik elektrifiering av vägtrafiken än att få publika snabbladdarstationer på plats, eftersom laddning vid hem och lastbilsdepåer utgör stommen i ett elektrifierat vägtransportsystem. Utmaningar och möjligheter med Vehicle-to-Grid-teknik (V2G) diskuteras. Rapporten belyser också osäkerheten kring framtida användning av förarlösa fordon och deras potentiella påverkan på laddningsbehov och trafikmönster. Prognoserna indikerar att det sammanlagda energibehovet för laddning av vägtransporter blir något lägre vintertid än sommartid, på grund av minskad trafik och trots ökad energiförbrukning vid låga temperaturer. Elvägar skulle endast ge ett ökat energibehov om de bidrar till en snabbare elektrifieringstakt, medan en storskalig användning av bränslecellslastbilar och lokalt producerad vätgas skulle ge en ökning av energibehovet på lång sikt med drygt 10% och på kort sikt mer, om fordonen endast ersätter förbränningsmotorfordon. Storskalig användning av syntetisk bensin och diesel framställd från grön vätgas bedöms som osannolik, men skulle kraftigt öka energibehovet så länge förbränningsmotorfordon fortfarande används.

We present a novel methodology for calculating the density of charging infrastructure required to enable electrification of all passenger cars in a large geographic region. We combine this method with models of charging infrastructure cost, forecasts of levelized costs for operating combustion engine and battery electric cars and forecasts of market penetration, to calculate the socio-economic value of passenger car electrification over the 2020-2040 period. Recommendations for urban regions are derived based on application of the method to Stockholm County, Sweden. Electrification is shown to generate long-term savings of up to 1800 euro per car-year and the opportunity cost of delaying the transition by a single year is comparable to the full cost of deploying the infrastructure that enables the shift. Large-scale deployment of dynamic charging is a cost-viable alternative to static charging for full electrification of urban passenger car fleets.

This report explores complex interaction effects between diesel-powered and battery powered heavy trucks, dynamic vehicle charging via electric roads, and static charging via other forms of charging infrastructure. The aim is to identify how these components of the future transport system should be jointly designed to simultaneously minimize the cost to society at the system level and meet society's need for greatly reduced greenhouse gas emissions from heavy road traffic. Focus is on investigating how an expansion of electric roads would affect the system and whether a national investment in electric roads can be assumed to have positive consequences that cannot be achieved at a lower cost using other means. Interaction effects are studied over time (2020–2050), geography (the entire Swedish road network), for four different truck weight classes and four types of charging infrastructure (electric roads, depot charging, destination charging and fast charging at rest stops).

The results are based on analyzes of hundreds of scenarios for the future expansion of charging infrastructure in Sweden. These scenarios have been analyzed using a custom built simulation tool, which simulates freight transport along millions of routes on the Swedish road network. For each individual route, vehicle class and year, battery capacity and charging locations are optimized to ensure sufficient battery capacity and to minimize the business economic cost of freight transport along the route. The capacity and partially placement of charging infrastructure is demand-driven, based on the aggregate demand from all transport routes. User charges for charging are calculated individually for different charging infrastructure sites based on estimated usage, in competition with other charging infrastructure, and are fed back to influence the choice of charging method along transport routes. Driving patterns, used combinations of charging infrastructure, capacity of battery packs in vehicles and changing battery technology over time are used to dynamically calculate the life cycle cost of vehicle batteries. Today's tax revenue from fuel sales is converted into a kilometer tax that is applied equally to both diesel and battery electric vehicles.

Route-based simulated traffic data for high-resolution analysis of heavy goods transport on the Swedish road network In this report, a national database has been created regarding freight transport with heavy road vehicles. The primary purpose of the work is to serve as input for further analysis of what appropriate charging infrastructure planning and placement should look like given the knowledge of the transport work. It has thus been no ambition to give any recommendations in this report about, for example, expansion of charging infrastructure, but rather to collect and process information/data as well as develop methods and finally generate a data set that is useful and well representative of the traffic on the national road network. By the time of this publication, a dataset is available based on data from the Swedish Transport Administration’s Samgods-model with its simulations of transport connections based on transport demand between producer and consumer zones. In addition, all transport connections have been translated into routes (how trucks drive from A to B) on the road network, to enable analysis of electrification of/at specific road segments. Finally, the dataset has also been calibrated in various ways to better match statistics and actual measurements, as some major differences/deviations compared to some of them were identified. What the data set now consists of can be summarized as the number of truck movements and tons of goods that annually pass each road segment of the Swedish road network (and on some foreign roads). Furthermore, these totals can be easily divided into subsets and linked to specific routes, types of trucks (weight classes), origin, etcetera. Some shortcomings/limitations have been noticed during the production of this data set, such as the fact that the Samgods-model seems to miss a lot of transport in metropolitan areas, that the routing carried out by all flows is not completely perfect (which has partly to do with requests from OpenStreetMap), that the methods for generating new routes based on population density within municipalities are unlikely to be fully representative of where the transport is going, or that the data itself is based on a simulation model that tries to optimize which type of transport should be used to meet which demand. A couple of additional things may be worth clarifying: (1) The data only tells the number of transports or shipped goods between start and end nodes. Thus, there is no way to determine what the movement pattern of individual vehicle individuals looks like between routes, nor when in time each transport is performed. (2) The data only includes freight transport, and thus "misses" for example all passenger car traffic, which should also be seen as potential users of the charging infrastructure and thus be included in the calculations in the future. It would therefore be interesting to include these in some way in the next step.

For the County of Stockholm (1 million cars), we calculate the cumulative socio-economic result of a gradual transition to a battery-electric fleet of passenger cars, over the period 2020-2040. Included in the analysis are the direct and indirect costs to deploy necessary charging infrastructure, and the value generated from lowered emissions and operational costs of vehicles. Necessary charging infrastructure investments are derived from a network model of mobility in the city, that ensures sufficient infrastructure to power all passenger cars. The most important conclusions are that cities should prioritize speed of transition rather than cost minimization to maximize cumulative return on investment, due to substantial cumulative cost savings from electrification, and that current undertaxation of fossil greenhouse gas emissions greatly reduces profit margins for private investments contributing to vehicle electrification. We estimate that a total cumulative infrastructure investment of 13 billion SEK can lead to electrification of 90% of the traffic work by passenger cars in Stockholm county by 2030. This would reduce cumulative system costs by 100 billion SEK from 2020 to 2030, with a return on infrastructure investment of 750%. Approximately 50% of this value is from externalized CO2 emission costs.