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Flagship Project: EV50

Car, gas pump riding on a bed of molecular structures

EV50 is a Bits & Watts flagship program designed by Stanford faculty and Bits & Watts industry members to understand the engineering, economic and policy implications of the dramatic transformation of our transportation fleets to 50% electrification and beyond.

Imagine we are in 2030. Electrification of land-based personal transportation globally is racing to 50 percent, as trucks and freight trains near 20 percent. The 2030 electric vehicle fleets include bikes, cars, buses and passenger trains. The vehicles are sometimes autonomous. Ridesharing is much more common than today. These vehicles vary in their performance characteristics, particularly in their range. Affordable and plentiful clean electricity powers these vehicles to meet stringent policy requirements worldwide. Recharging happens at home, at work, at charging stations in shopping lots and gas stations. The speed of charging has improved significantly, ensuring that high daily mileage—like those of long and short haul trucks—can happen with ease.

Several critical challenges need to be addressed to enable this future. 

Scaling the grid for charging:

Charging will place significantly higher energy and power demands on the grid. Managing this will require coordination of charging in transmission and distribution grids to ensure reliability and efficiency. Coordination is difficult because it requires mediating between the goals of multiple market participants while incorporating physical power network and cyber communication network constraints. Particular importance needs to be paid to economic signals that inform buyers, sellers and system operators of local grid conditions. Dynamic and granular pricing in distribution networks could provide such a signal. Given the expected growth in charging, alternative system designs such as DC power distribution networks could prove to be economically viable. 

Some key questions on scaling:
• Can we quantify the grid impact of future charging demand?
• How can we design a simple and efficient signaling mechanism?
• Can we create a scalable strategy for reliable coordination?
• What are some alternatives when planning future transmission and distribution systems?

Networking technologies for charging:

Connected cars and devices will provide opportunities to collect data to predict and shape charging demand. Networks of such devices could help manage charging, yet this requires significant flows of information between the devices and systems responsible for coordination.

Some key questions on networking:
• What is the role these technologies can play in coordination?
• How can we design secure and private information sharing mechanisms that will be necessary for their participation in coordination strategies?

Business models and engineering charging:

Charging speeds available in the near future will be dramatically higher than current standards. A variety of use cases will emerge, including charging fleets of ridesharing vehicles, buses and trucks. The charging network design will influence the strategies forcharging vehicles. For example, fleets in the future will require designing routes that will need to consider charging needs, electricity costs, transportation demands and traffic.

Some key questions on business models:
• Can we invent efficient route planners?
• How should we design charging stations and networks?
• What is the business model and charging ecosystem that will evolve around them?
• How will consumer convenience and charging choice shape future charging demand?

Electric vehicle technology and its impact:

The evolution of battery packs in electric vehicles will enable faster charging. Each battery system technology has a unique charging profile, which impacts the pack’s health and lifetime. More realistic models of the battery system will be needed to enable and scale future charging. As battery systems age and lose capacity they are removed from vehicles. It is predicted that by 2030, we will have 1TWh of retired battery capacities. Also, vehicle fleets are expected to have varying degrees of autonomy.

Some key questions on technology:
• Can we build realistic models of charging based on data collected from real systems in realistic drive cycles?
• How should we incorporate these models into charging management?
• Can these batteries be utilized for grid storage?
• What role can they play in the coordination of charging demand?
• How does autonomy affect charging?