The planet is facing a climate change crisis, and we have a responsibility to reduce greenhouse gas (GHG) emissions and abate the destructive effect rising temperatures have on the earth and the global economy. Almost one-third (29%) of U.S. GHG emissions are generated by transportation, and medium-duty (MD) and heavy-duty (HD) vehicles make up almost a quarter (23%) of the transportation sector. With this in mind, the commercial vehicle (CV) industry must be on the front line of decarbonization.
Electric vehicle (EV) innovations are making batteries more affordable, extending vehicle range and producing more purpose-built platforms — all within in a relatively short time span. Consider the fact that diesel engine development has spanned 130 years, while development of battery electric vehicles (BEVs) at scale has been an automotive focus for less than a decade.
Even with this progress, however, as we look to the future of EVs in the logistics industry, we are starting to see some long-term challenges, especially when compared to diesel vehicles:
- The cost of electric vehicles and the supporting infrastructure are substantial, straining the financial viability of fleets, especially smaller operators with fewer vehicles.
- EV usage is currently limited by the number of routes that will accommodate electric CVs, and the volume of load an EV can transport.
- Prolonged charging time reduces asset productivity and is problematic for conventional driver compensation. Ultimately, fleet operating models will have to be revised to address EVs.
- Lack of parking and charging station availability impedes electrification.
- Working with utilities is difficult and lead times for EV infrastructure deployments outpace normal lead times for asset purchases many times over.
All of these impediments, combined with negative public debate about EVs, increase the perceived risk as fleets migrate from diesel to electric vehicles. In particular, fleets are becoming less concerned about EV availability and more concerned about the capacity of the charging infrastructure and electric grid to handle electrification of MD and HD vehicles.
Modeling a Complete Transition to BEVs
To delve deeper into this topic, Roland Berger modeled a 100% build out case for electrification of all U.S. Class 3-8 commercial vehicles. The objective was to ascertain the total investment required for the infrastructure build out for vehicle charging — as well as electricity distribution, generation and transmission — to support a complete transition of U.S. Class 3-8 commercial vehicles to BEVs.
This study was not intended to project how BEV adoption would grow, but rather to determine the cost to convert the entire U.S. fleet from diesel to electric vehicles based on plausible, conservative expectations.
The Roland Berger model considered three basic charging locations:
- On-site charging — Privately owned chargers at the fleet's locations, as well as shared charging hubs with dedicated availability for commercial vehicles, providing a mix of L2, L3 and, in limited cases, DCFC chargers.
- Local on-route charging — High-mileage local applications offering public access to DCFC chargers.
- On-route highway charging — DCFC chargers as well as L2 and L3 chargers used for charging long-haul vehicles overnight.
For the local charging network simulation, we used fleet telematics data from NREL to analyze Class 3-8 vehicle operation during the day, excluding long-haul trucks. We used the mileage distribution and duty cycle to determine the charging resources required across overnight depot and on-route “top-up” charging. Aggregating average load curves per vehicle class, combined with the regional allocation of vehicles per weight class, allowed us to simulate charging infrastructure and load curves at the county level.
For the on-route highway charging network simulation, we evaluated the existing distribution of refueling stations throughout the U.S. highway network. We also used route-specific truck traffic data to calculate how many long-haul vehicles would be recharging at each location, differentiating between top-up and overnight charging. Based on this data, we determined the investment required to deploy vehicle charging infrastructure at each station. Again, this allowed us to simulate charging infrastructure and load curves at the county level.
Calculating the Cost
Estimating a usable range for Class 6-8 trucks at 250 miles and DCFC chargers of 500 kW for local on-route charging and 1 MW for highway charging, the Roland Berger model calculated that a total investment of $620 billion will be required for chargers, site infrastructure and utility services. On-site charging with L2 and L3 chargers constitutes the majority of the cost at roughly $500 billion. On-route charging investments are almost equally divided between local 500 kW chargers (USD 69 bn) and on-highway 1 MW chargers (57 bn).
The cost of local charging is driven mostly by HD vehicles that need L3 or even DCFC charging at their depot. The charging infrastructure is three times as expensive on a per vehicle level for HDs (approximately $145,000) then for MDs (approximately $54,000).
In addition, distribution grid upgrades and new builds are expected to cost utilities about $370 billion to meet the local charging demand from MDHD vehicles. More regulatory support and practical grid planning will be necessary to avoid bottlenecks and delays. Since utilities tend to keep rates low and ensure affordability for customers, funding for these upgrades will also be an issue.
The investment required for energy production and distribution will cost an additional $44 billion, per the Roland Berger model. However, this investment is already factored into the utilities' long-term roadmap.
The overall price tag of almost $1 trillion demonstrates the imposing challenge the logistics industry will face when advancing from internal combustion engines (ICE) to BEV. In addition, the high BEV prices and operational issues will impact the total cost of maintaining a fleet of BEV trucks even more.
Taking on the Challenges
How can the logistics industry address the challenges revealed by the Roland Berger study?
First, fleet operation must be continuously optimized. While this study-based BEV fleet operation on the same model used for conventional trucks, BEV fleets must actually improve operations by leveraging route planning and managed charging to counteract the limitations of BEVs. OEMs, fleets, utilities and regulators must collaborate to find appropriate use cases and expedite build out of the necessary infrastructure. Escalated improvement of technical performance would also help reduce costs.
Second, roll out of electrification in MDHD must be in phases. The initial focus should be on use cases that minimize operational costs. In Roland Berger's view, there are MD use cases and HD use cases along specific highway corridors that are candidates for early adoption.
Third, we must use a technology-agnostic approach to find cost-effective solutions. Other decarbonization options are available. For example, certain use cases or routes may be more cost-effectively served by alternatives such as renewable diesel.
And finally, we cannot expect this transformation to be financed by transport operators, since the U.S. logistics industry has annual revenues of about $800 billion with minimal profits. Private capital may be the ideal method to finance the charging infrastructure, but government support — such as targeted incentives and regulation — is presumably needed until BEV technology and business model improvements deliver a cost advantage over ICE vehicles.
The logistics industry strives to maintain safe, economical and sustainable transportation of cargo. Electrification can help fleet operators meet this commitment, and BEVs are ideally positioned for widespread adoption across commercial vehicle fleets. As we set expectations, make decisions and implement policies to guide the transition from BEV to ICE, we must consider the challenges faced by fleets and other industry stakeholders while establishing ambitious yet achievable goals and timelines.
