Objective 1: develop model-based, flexible, modular, cost-effective battery management technologies based on an in-depth understanding of the internal state of the battery enabling pro-active control at the cell-level.
The EVERLASTING partners selected a Li-ion battery cell (18650 NMC chemistry) characterized in detail via performance/ageing tests executed by VITO and TUV SUD. Ageing tests (life/drive cycling & calendar ageing) using representative charge/discharge profiles, provided data supporting battery modeling & BMS algorithms research.
TUM and TU/e developed reduced electrochemical models taking into account modelling errors vs calculation time. VITO studied machine learning techniques to improve the accuracy of SOC/SOH algorithms.
Siemens made significant progress on virtual test benches development within Simcenter Amesim supporting advanced BMS research & development. This tool allows a fast & efficient way to consider battery ageing when developing BMS strategies, deal with subsystems faults and ways to protect the battery.
LION Smart developed a new BMS (hardware-software-interfaces) based on the needs of the EVERLASTING technologies. A BMS master-slave configuration was designed, tested and implemented in a full-size 40 kWh demonstrator battery pack, installed in VOLTIA’s electric van. The demonstrator battery pack was integrated using a battery swap procedure.
The VOLTIA battery pack demonstrator allowed validation of LION Smart Standardized BMS architecture, RWTH battery Flexible operating range and Online-EIS, CEA thermal runaway multiphysics sensors and ALGOLiON safety diagnostic algorithms predicting safety hazards.
Thermal runaway precursor detection is a key point to improve safety. The capacity to detect those precursors was evaluated & demonstrated at early stage (ALGOLiON’s early warning diagnostic algorithm based on battery voltage and current measurements) and at middle and late stage (CEA strain sensors). To support this development, TUV SUD defined a safety testing toolset & conducted lab safety tests. Some test methods were improved e.g. the abuse method to create a soft internal short circuit.
To improve battery lifetime, thermal and load management strategies were studied. For the thermal management a combined active/passive cooling solution was evaluated on a lab test setup by CEA. For the load management strategies, evaluation by TUM focused on dissipative balancing with promising results.
EVERLASTING aimed to extend driving range at same battery size without impacting user comfort by expanding battery’s operational envelope within the safety limits combined with driveline energy management. VDL ETS, with TU/e support, developed & validated models using a VDL Citea SLFe-120 electric city-bus via extreme climate & aerodynamic tests, achieving good results on lowering errors on range estimation and on increasing driving range.
Objective 2: develop standardized BMS architecture & BMS reliability testing procedures.
Existing BMS standards & standardization potential of EVERLASTING BMS architectures were studied. Information is shared via a standardization workshop, contacts with standardization bodies and the EVERLASTING website (
https://everlasting-project.eu/results/(s’ouvre dans une nouvelle fenêtre)).
EVERLASTING Dissemination: 37 journal publications, 20 peer reviewed & 33 non-peer reviewed conference publications, 2 PhD thesis, 14 public events & 33 public deliverables (of which 13 white papers). EVERLASTING participated in the Open Research Data Pilot (ORDP) & 27 open datasets were shared on 4TU.ResearchData repository.