Energy

Artificial Intelligence for Battery Reuse, Recycling and Remanufacturing

Tao, Shengyu
Scott Moura
Brandell, Daniel
Han, Zhiyuan
Urréhman, Shafiq
Zou, Changfu
Zhang, Xuan
Zhou, Guangmin
2026

Lithium-ion batteries are often retired while still retaining 70–80% of their rated capacity, creating economic and environmental challenges across their supply chain. Although reuse, recycling and remanufacturing offer alternatives to recover this otherwise under-utilized value, their implementation is hindered by the lack of reliable data on battery condition at retirement, making it difficult to determine whether, when and how these alternatives should be applied. In this Perspective, we discuss how artificial intelligence (AI) can help to overcome data barriers by enabling adaptive,...

CAR-EnKF: A Covariance-Adaptive and Recalibrated Ensemble Kalman Filter Framework

Jiang, Shida
Tao, Shengyu
Liu, Zihe
Scott Moura
2026

The ensemble Kalman filter (EnKF) is widely used for nonlinear and high-dimensional state estimation because it replaces complex covariance propagation with simple ensemble statistics. However, conventional EnKF implementations can become overconfident in the presence of measurement nonlinearity. The commonly used covariance inflation technique only partially alleviates this issue. This paper proposes a covariance-adaptive and recalibrated ensemble Kalman filter (CAR-EnKF) framework for nonlinear state estimation. The framework introduces two improvements that are only active for nonlinear...

Design Guidelines for Nonlinear Kalman Filters via Covariance Compensation

Jiang, Shida
Lee, Jaewoong
Tao, Shengyu
Scott Moura
2026

Nonlinear extensions of the Kalman filter (KF), such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are indispensable for state estimation in complex dynamical systems, yet the conditions for a nonlinear KF to provide robust and accurate estimations remain poorly understood. This work proposes a theoretical framework that identifies the causes of failure and success in certain nonlinear KFs and establishes guidelines for their improvement. Central to our framework is the concept of covariance compensation: the deviation between the covariance predicted by a...

Model-Agnostic Energy Throughput Control for Range and Lifetime Extension of Electric Vehicles via Cell-Level Inverters

Jiang, Shida
Tao, Shengyu
Molina, Vincent
Shi, Junzhe
Scott Moura
2026

A conventional electric vehicle (EV) powertrain relies on a centralized high-voltage DC-AC inverter, thereby limiting cell-level control and potentially reducing overall driving range and battery lifetime. This paper studies an H-bridge-based cell-level inverter topology that performs power conversion at the cell level, enabling independent control of individual cells and expanding the design space for battery management. Leveraging these additional degrees of freedom, we propose a model-agnostic energy-throughput control strategy that extends EV range while improving battery-pack lifetime...

(U)NFV: (Un)Supervised Neural Finite Volume Methods for Solving Hyperbolic PDES

Lichtle, Nathan
Canesse, Alexi
Fu, Zhe
Matin, Hossein Nick Zinat
Maria Laura Delle Monache
Alexandre Bayen
2026

We introduce (U)NFV, a modular neural network architecture that generalizes classical finite volume (FV) methods for solving hyperbolic conservation laws. Hyperbolic partial differential equations (PDEs) are challenging to solve, particularly conservation laws whose physically relevant solutions contain shocks and discontinuities. FV methods are widely used for their mathematical properties: convergence to entropy solutions, flow conservation, or total variation diminishing, but often lack accuracy and flexibility in complex settings. Neural Finite Volume addresses these limitations by...

Defining An Accuracy Limit in Battery State Estimation

Jiang, Shida
Tao, Shengyu
Lee, Jaewoong
Scott Moura
2026

Batteries are everywhere in our daily lives. Their applications span from electronic devices to electric vehicles (EVs) and further to grid-scale energy storage systems. Accurate battery state of charge (SOC) and state of health (SOH) estimations are essential elements of a battery management system (BMS) that ensure the safe and efficient operation of various battery-powered equipment. SOC describes the remaining charge of the battery. It is defined as the ratio of the instantaneous remaining capacity to its present maximum capacity....

Hydrogen-Energy-Stations

Tim Lipman
Cameron Brooks
2006

The “hydrogen energy station” is one method of hydrogen production at small and medium scales. Unlike more conventional hydrogen station designs where hydrogen is simply delivered or produced on-site with a fuel “reformer” or water electrolyzer and then compressed and dispensed, energy stations would provide multiple functions in the same facility. They would integrate systems for production of electricity for 1) local uses and/or the utility grid, 2) re-use of thermal energy “waste heat” for building heating/cooling needs, and 3) purified hydrogen for refueling vehicles. Hydrogen energy...

An Overview of Hydrogen Production and Storage Systems with Renewable Hydrogen Case Studies

Tim Lipman
2011

Hydrogen is already widely produced and used, but it is now being considered for use as an energy carrier for stationary power and transportation markets. Approximately 10-11 million metric tonnes of hydrogen are produced in the US each year, enough to power 20-30 million cars or 5-8 million homes.1 Major current uses of the commercially produced hydrogen include oil refining (hydro-treating crude oil as part of the refining process to improve the hydrogen to carbon ratio of the fuel), food production (e.g., hydrogenation), treating metals, and producing ammonia for fertilizer and other...

Plug-In Electric Vehicles in California: Review of Current Policies, Related Emissions Reductions for 2020, and Policy Outlook

Maggie Witt
Matthew Bomberg
Tim Lipman
Brett Williams
2012

California's emissions reduction goals for criteria air pollutants (CAPs) and greenhouse gases (GHGs) have encouraged policies that support plug-in electric vehicles (PEVs). This paper explores current and planned policies that promote PEVs, potential emissions benefits from PEV adoption in California by 2020, and future policy directions. The reviewed policies include the zero-emission vehicle regulations, the low-carbon fuel standard, and the clean car standards, which all require GHG reductions. Policies prompted by the California Public Utilities Commission Alternative-Fueled Vehicle...

Strategy for Overcoming Cost Hurdles of Plug-In–Hybrid Battery in California: Integrating Post-Vehicle Secondary Use Values

Brett Williams
Tim Lipman
2010

Advances in electric drive technology, including lithium ion batteries as well as the development of strong policy drivers such as California's Global Warming Solutions Act, now contribute to a more promising market environment for the widespread introduction of plug-in vehicles in California. Nevertheless, battery costs remain high. This study explores a strategy for overcoming the significant hurdle to electric transportation fuel use presented by high battery costs. It describes offsetting plug-in-vehicle battery costs with value derived from post-vehicle stationary use of hybrid...