No abstract

The temperature and the temperature gradient within the battery pack of an electric vehicle have a strong effect on the life time of the battery cells. In the case of automotive applications, a battery thermal management (BTM) system is required to maintain the temperature of the cells within a prescribed and safe range, and to prevent excessively high thermal gradients within the battery pack. This work documents the assessment of a thermal management system for a battery pack for an electric van, which adopts a combination of active/passive solutions: the battery cells are arranged in a matrix or composite made of expanded graphite and a phase change material (PCM), which can be actively cooled by forced air convection. The thermal dissipation of the cells was predicted based on an equivalent circuit model of the cells (LG Chem MJ1) that was empirically calibrated in a previous study. It resulted that, in order to keep the temperature of the battery pack at or below 40 °C during certain charge/discharge cycles, a purely passive BTM would require a considerable amount of PCM material that would unacceptably increase the battery pack weight. Therefore, the passive solution was combined with an air cooling system that could be activated when necessary. To assess the resulting hybrid BTM concept, CFD simulations were performed and an experimental test setup was built to validate the simulations. In particular, PCM melting and solidification times, the thermal discrepancy among the cells and the melting/solidification temperatures were examined. The melting time experimentally observed was higher than that predicted by the CFD model, but this discrepancy was not observed during the solidification of the PCM. This deviation between the CFD model results and the experimental data during PCM melting can be attributed to the thermal losses occurring through the mock-up casing as the heating elements are in direct contact with the external walls of the casing. Moreover, the temperature range over which the PCM solidifies was 6 °C lower than that estimated in the numerical simulations. This occurs because the simple thermodynamic model cannot predict the metastable state of the liquid phase which occurs before the onset of PCM solidification. The mockup was also used to emulate the heat dissipation of the cells during a highway driving cycle of the eVan and the thermal management solution as designed. Results showed that for this mission of the vehicle and starting from an initial temperature of the cells of 40 °C, the battery pack temperature could be maintained below 40 °C over the entire mission by a cooling air flow at 2.5 m/s and at a temperature of 30 °C.

No abstract

This paper presents a comprehensive survey of state-of-the-art intelligent fault detection and diagnosis in district heating systems. Maintaining an efficient district heating system is crucial, as faults can lead to increased heat loss, customer discomfort, and operational cost. Intelligent fault detection and diagnosis can help to identify and diagnose faulty behavior automatically by utilizing artificial intelligence or machine learning. In our survey, we review and discuss 57 papers published in the last 12 years, highlight the recent trends, identify current research gaps, discuss the limitations of current techniques, and provide recommendations for future studies in this area. While there is an increasing interest in the topic, and the past five years have shown much advancement, the absence of open-source high-quality labeled data severely hinders progress. Future research should aim to explore transfer learning, domain adaptation, and semi-supervised learning to improve current performance. Additionally, a researcher should increase knowledge of district heating data using data-centric approaches to establish a solid foundation for future fault detection and diagnosis in district heating.

A well performing District Heating Substation (DHS) is crucial for the efficiency of the District Heating (DH), especially with the shift towards low temperature 4th generation DH systems. For this reason, testing and characterization of commercially available DHSs becomes important to estimate their effect on the DH network. Within the thermo-technical laboratory of EnergyVille, a multipurpose test rig has been built for testing DHSs. In this setup, different DH conditions and heat demand profiles for space heating and for Domestic Hot Water (DHW) can be emulated. Independent tests have been performed on 4 DHSs from three different manufacturers, focused on the DHW preparation for low DH supply temperature and on the stand-by/keep-warm operation of the substations. The latter maintains a certain temperature within the heat exchanger to avoid delays in the delivery of DHW. The results showed that improvements are needed on DHW production for lower DH supply temperatures. Also, enhancements are needed to reduce losses from the keep-warm function. Given that DH systems can have thousands of substations, this will reduce the overall losses and improve the performance of the DH network.