SUPR
Vehicle battery storage for green transport and grid stability in the Nordics
Dnr:

NAISS 2025/22-576

Type:

NAISS Small Compute

Principal Investigator:

Wendi Guo

Affiliation:

Uppsala universitet

Start Date:

2025-04-07

End Date:

2026-05-01

Primary Classification:

20304: Energy Engineering

Allocation

Abstract

Best4Grid aims to advance green transport and vehicle-to-everything (V2X) technology by delivering technical solutions, a unified legislative framework, business strategies, and a tailored roadmap for the Nordic region. The project focuses on analyzing the impact of V2X on battery efficiency and aging, promoting sustainable energy usage and grid stability. Key thematic areas include: Smart Energy System: By integrating the transportation sector with the electric grid, the project enhances energy efficiency while minimizing battery degradation. Optimized V2X solutions will reduce environmental impacts, extend battery lifespan, and lower the demand for battery replacements. Project Contribution: The project delivers innovative solutions for onboard energy management, minimizing battery degradation under realistic cycling conditions. This will enable large-scale EV deployment while enhancing grid stability, accelerating the transition toward sustainable, electrified transport in the Nordics. Green Transport: Best4Grid supports transportation electrification by developing strategies to mitigate battery degradation, enabling longer battery life and more sustainable transport solutions. Robust battery aging predictions will drive the adoption of EVs and energy storage systems. In the onboard energy management work package, the Ångström Advanced Battery Centre (ÅABC) at Uppsala University, the largest academic battery research environment in the Nordics, will lead battery modeling efforts. Postdoc fellow Wendi Guo will develop electrochemical models using finite element methodology to predict battery aging under V2X conditions. These models will integrate with thermal simulations, in collaboration with DTU, and scale up to pack-level using equivalent circuit modeling. This approach will link vehicle energy consumption with battery aging, facilitating system-level energy optimization in partnership with Scania.