NEXT-generation physics and data-based Battery Management Systems for optimised battery utilization

Project Information

NEXTBMS

Grant agreement ID: 101103898

DOI

10.3030/101103898

EC signature date 28 March 2023

Start date 1 June 2023

End date 31 May 2027

Funded under

• Climate, Energy and Mobility

Total cost

€ 4 998 318,25

EU contribution

€ 4 998 318,25

Coordinated by

AIT AUSTRIAN INSTITUTE OF TECHNOLOGY GMBH
Austria

Periodic Reporting for period 2 - NEXTBMS (NEXT-generation physics and data-based Battery Management Systems for optimised battery utilization)

Reporting period: 2024-12-01 to 2026-05-31

Summary of the context and overall objectives of the project

NEXTBMS is to achieve a best-in-class advanced BMS hard- and software solution concerning technical performance, adaptiveness, and cost, for first life perspective as well as end-of-life (second life) management.
The overall objectives of NEXTBMS are:
1) Increased battery utilisation with relation to operational limits (i.e. increasing the battery's usable SoC window, increasing its maximum full equivalent cycles, enabling fast charging at low and high outside temperatures) and overall energy throughput over lifetime (incl. first and second life, and recycling).
2) Shortened the time-to-market for new battery packs, operating with new and novel battery chemistries, by means of scalability and fast parameterisation of battery cell models with only minimal a priori knowledge of the characterisation of the cells.
3) Maintaining the high level of safety and reliability status of battery systems especially in enhanced operation conditions and during end-of-life management incl. second life applications.
4) Demonstrated enhanced BMS performance via a single battery module with complete functionality.

NEXTBMS will for the first time enable consistent simulation of electrochemical phenomena in battery management. It will use advanced physics-based models which run partly on the on-board BMS and partly in the cloud. AI models will be used to adapt parameters of the physics-based model and to analyse the big data on the cloud. This ultimately leads to improved physical and safety related battery state estimations during operation. These more precise internal cell states and derived overall battery system states help to enhance battery utilisation and to minimize internal energy losses. This directly improves the BMS calibration boundaries that are currently set with conservative values leading to suboptimal utilization.

Pathway to impact:
On the economic impact, the first step for the industrial partners in the two years after the project is to raise the advanced BMS to TRL 5-7 and from there to TRL 8 and 9. This involves amongst others the extensive demonstration of prototypes in a relevant environment, qualifying the implementation of the NEXTBMS in the design and production of future battery cells and packs. Furthermore, the project partners will establish commercial relations with ≥ 5 suppliers and ≥ 3 OEMs, among others for the licensing of IP and technology and will expect to use the generated outcome also in their own products on battery and BMS testing on battery test benches. The potential impact in the five years after the project is the roll-out of the innovative BMS solutions in the growing EV automotive sector.

On the societal front, the first steps are to involve policy makers and the European public. Once the NEXTBMS project is completed, concrete steps can be taken in the further development of new generation BMSs. The consortium will inform policy makers and European (battery project) platforms like BATT4EU and BRING, so they can assess the information (e.g. to get a better view on the impact of future enhanced physiochemically BMS models) and adjust future research calls or guidelines in their policies. By promoting the innovations, the European public can learn what has been achieved, and what these innovations mean for the battery cells and battery packs that will become available on the market.

On the scientific front, the research partners will take the NEXTBMS innovations and develop them further for other battery management systems for other applications, such as the elaboration of the approach (applying equivalent circuit models with physicochemical consistency for batteries) to make it more applicable (bring it to a higher TRL > 4), to improve the quality of battery passports regarding failures and availability of mission critical data, and to provide a more reliable system. Also, thanks to its accessibility and growth potential, the NEXTBMS battery management enhanced circuit model will result in the knowledge transfer in advanced BMS modelling and HW development and open a direct pathway between researchers and industrial partners. The exploration of NEXTBMS’s systems supports EU applied research activities and the development of flexible and adaptable BMS topologies, components, data links and control standards as a common basis for efficient development pipelines and final cost benefits for every kind of user in the entire society.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Summary of the activities and main achievements (for PR2) towards the three technical objectives (TO), defined in Annex 1:

Progress towards TO 1: Advanced physics-based and adaptable battery models
During PR2, significant progress was achieved in WP2 through the completion and parameterisation of both the computationally efficient BMS model and the sophisticated cloud model. The model parameterisation was based on comprehensive experimental characterisation data generated within the project, including GITT measurements, electrochemical impedance spectroscopy (EIS), ageing tests, and half-cell analyses.
A major achievement was the successful deployment of the electrochemical model on the Infineon AURIX TC375 microcontroller. Advanced diagnostic functionalities were further developed within the cloud environment, including parameter identification from discharge curves and EIS measurements, degradation analysis based on Loss of Lithium Inventory (LLI) and Loss of Active Material (LAM), and advanced State-of-Health estimation methods. The developed diagnostic framework was successfully validated using experimental ageing data generated within NEXTBMS.
In parallel, WP2 and WP4 collaborated on preparing the integration of the developed models into the future validation environment, and virtual upscaling activities and battery pack simulations were completed.

Progress towards TO 2: Advanced data acquisition combining sensor-based solutions and model-generated information
During PR2, major progress was achieved in WP3 through the finalisation of the innovative sensor-integrated battery module concept. Multiple sensing technologies were successfully integrated into the demonstrator modules, including fibre-optic strain and temperature sensors, PT1000 temperature sensors, large-area sensing foils, piezoelectric force sensors, and electrochemical impedance spectroscopy measurement hardware.
The mechanical and electrical integration of the sensor systems was completed and validated through dedicated calibration and testing activities. In parallel, the data acquisition infrastructure and synchronised measurement software were finalised, enabling synchronized acquisition of all sensor signals.
Further progress was achieved regarding EIS-based sensing functionalities. Dedicated experimental campaigns were conducted to evaluate the suitability of EIS measurements for lithium-plating detection and thermal gradient identification under representative operating conditions. Additional test benches combining advanced EIS hardware and reference measurement systems were successfully established and operated.
At the system level, the NEXTBMS hardware architecture was finalised. This included completion of the daughter boards for cell monitoring, balancing and EIS measurements, the slave controller architecture, the AURIX-based master controller, and the battery protection electronics.

Progress towards TO 3: Advanced control algorithms, state estimation and validation of the NEXTBMS concept
During PR2, progress was achieved regarding the development of the advanced SoX functionalities. State-of-Charge (SoC), State-of-Health (SoH), and State-of-Function (SoF) algorithms were completed and verified using Model-in-the-Loop test environments. The developed algorithms combine measured signals, model-generated information, ageing corrections, and battery operating constraints to enable state estimation and control.
Cloud-based functionalities were further developed through the definition and implementation of the NEXTBMS edge-to-cloud architecture. Dedicated use cases were established for physics-based model reparameterization, Remaining Useful Life (RUL) estimation, and real-time battery data streaming. The cloud infrastructure, communication framework, and security architecture were defined and prepared for demonstrator integration.
The RUL framework was further enhanced using experimental NEXTBMS ageing data and extended towards module-level prediction capabilities. In parallel, cloud-based physics-informed degradation modelling activities progressed through the implementation and calibration of ageing sub-models.
Within WP4, comprehensive preparations for the upcoming validation phase were completed. Detailed Hardware-in-the-Loop test plans were established for both automotive and stationary applications, virtual battery pack validation was performed using the Open Vehicle Powertrain Platform, and dedicated HiL infrastructures were prepared at EDF and TNO.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Not yet applicable.