Data-Driven Degradation monitoring and prediction of BATteries for Maritime ApplicatioNs


Dr Erik Vanem, DNV GL, Norway


Large scale enterprise

Research institute


Large scale enterprise

Project Abstract

The use of battery systems for onboard energy storage is an attractive alternative for many shipping segments, both from an economic perspective with significant potential for cost savings, but also from an environmental, regulatory and societal perspective. However, the safety of battery-powered ships must be ensured. One critical aspect is the ability to deliver, at any time during operations, the power demand for safe and reliable propulsion, maneuvering and operation. Failure to do this may lead to intolerable accidents with severe consequences. Thus, a reliable estimation and prediction of the available energy stored in the battery at any time is of paramount importance.

One of the objectives of this project is to develop data-driven methods for prognostics of battery systems and to provide means for verifying the battery state of health (SoH) based on real-time sensor measurements. Currently, such validation is based on an annual capacity test, which has several limitations. The test typically requires the ship to be taken temporarily out of service and it is believed that more accurate and reliable estimates of SoH can be obtained based on continuous sensor measurements so that variability in loads, temperatures and depth of discharge can be taken into account.

Operational data are needed, and these will be collected in the project from ships in operation, and reliable and secure strategies for data collection, storage and sharing will be addressed. Moreover, additional insight will be obtained from laboratory testing under variable conditions. Focus will be on aspects related to battery systems for cruise ships, including battery lifetimes, replacement strategies, life cycle assessment and shore connection procedures. The project will set new standards for reliability and lifetime prognostics and deliver recommendations and give input to standards, recommended practices and class rules and main project results and findings will be reported in scientific publications.

The main objective of this project is to explore and develop data-driven approaches for modelling the SoH in real-time or near-real-time to facilitate real-time monitoring of state of degradation of batteries onboard ships. The idea is that continuous sensor data measuring relevant parameters such as temperatures, and discharge rates as well as impedance behavior and increase, provide useful information about the operating history of the battery system that can be used to model and forecast the degradation and thereby also the SoH at any time.

DDD-BATMAN is funded by the MarTERA partners Research Council of Norway (RCN) and German Federal Ministry of Economic Affairs and Energy (BMWi).

Project Start

April 2020

36 month
Project Budget

Total Cost: 1.9 M€
Funding: 1.1 M€