• Energy Research

This paper presents results obtained from extensive accelerated lifetime tests performed on a high power Lithium Titanate Oxide (LTO) battery cell. The tests were performed at elevated temperatures, with different C-rates, and for different cycle depths. The obtained results have shown a very good capacity retention and a reduced internal resistance increase (and subsequently reduced power capability decrease) even after more than 8000 cycles performed at 42.5°C. We found out that both the capacity and the internal resistance have been degrading faster when the LTO-based battery cells were cycled with a smaller C-rate (i.e., 1C) than with a higher C-rate (i.e., 3C). Moreover, based on the harvested aging results, we discovered that the capacity and not the internal resistance is the performance parameter of the tested LTO-based battery cells, which will limit their lifetime.

Wind turbine converters demand high power density due to nacelle space limitation and high reliability due to high maintenance cost. Depending on the converter structure, the converter thermal performance determines the converter power density and reliability. To estimate the converter thermal performance, the converter structure-based power loss and thermal models are developed in this study for the medium-voltage (MV) three-level active neutral-point-clamped voltage source converter (3L-ANPC-VSC) utilizing 4500 V-1800 A press-pack insulated-gate bipolar transistor-diode pairs and interfacing a 6 MW wind turbine to a MV grid. The switching power loss models are built using the experimental switching power loss data acquired via the double-pulse tests conducted on a full-scale 3L-ANPC-VSC prototype. The converter static thermal model is developed based on the double-sided water-cooled press-pack switches. Via a single-phase test setup with two full-scale 3L-ANPC-VSC legs, the developed power loss and thermal models are validated experimentally. Employing the validated models, the 3L-ANPC-VSC's thermal performance is demonstrated on simulation for a 6 MW wind turbine grid interface. Hence, these converter structure-based models developed and validated in this study are proven to be suitable for the converter power density and reliability studies based on converter thermal performance. Peer Reviewed

This paper proposes a low-complexity online state of charge estimation method for LiFePO4 battery in electrical vehicles. The proposed method is able to achieve accurate state of charge with less computational efforts in comparison with the nonlinear Kalman filters, and also can provide state of health information for battery management system. According to the error analysis of equivalent circuit model with two resistance and capacitance, two proportional-integral filters are designed to compensate the errors from inaccurate state of charge and current measurements, respectively. An error dividing process is proposed to tune the contribution of each filter to the finial estimation results, which enhances the validation and accuracy of the proposed method. Recursive least squares filter can provide the state of health information and updates the parameters of battery model online to eliminate the errors caused by parameters uncertainty. The proposed method is compared with extend Kalman filter in regards to accuracy and execution time. The execution time of the proposed method is measured on Zynq board platform to validate its suitability for online implementation. In this paper, the proposed method is able to obtain less than 1% error for state of charge estimation.

Lithium-ion batteries are regarded as the key energy storage technology for both e-mobility and stationary renewable energy storage applications. Nevertheless, Lithium-ion batteries are complex energy storage devices, which are characterized by a complex degradation behavior, which affects both their capacity and internal resistance. This paper investigates, based on extended laboratory calendar ageing tests, the degradation of the internal resistance of a lithium-ion battery. The dependence of the internal resistance increase on the temperature and state-of-charge level has been extensive studied and quantified. Based on the obtained laboratory results, an accurate semiempirical lifetime model, which is able to predict with high accuracy the internal resistance increase of the lithium-ion battery over a wide temperature range and for all state-of-charge levels, was proposed and validated.

The operation of distributed power generation systems under grid fault conditions is a key issue for the massive integration of renewable energy systems. Several studies have been conducted to improve the response of such distributed generation systems under voltage dips. In spite of being less severe, unbalanced fault cause a great number of disconnections, as it may produce the injection of unbalanced currents that can easily conduct to the tripping of the converter. In this paper a current control strategy for power converters able to deal with these grid conditions, without exceeding the current ratings of the converter is introduced. Moreover, a novel flexible algorithm has been proposed in order to regulate easily the injection of positive and negative currents for general purpose applications. Peer Reviewed

Applications of lithium-ion batteries are widespread, ranging from electric vehicles to energy storage systems. In spite of nearly meeting the target in terms of energy density and cost, enhanced safety, lifetime, and second-life applications, there remain challenges. As a result of the difference between the electric characteristics of the cells, the degradation process is accelerated for battery packs containing many cells. The development of new generation battery solutions for transportation and grid storage with improved performance is the goal of this paper, which introduces the novel concept of Smart Battery that brings together batteries with advanced power electronics and artificial intelligence (AI). The key feature is a bypass device attached to each cell that can insert relaxation time to individual cell operation with minimal effect on the load. An advanced AI-based performance optimizer is trained to recognize early signs of accelerated degradation modes and to decide upon the optimal insertion of relaxation time. The resulting pulsed current operation has been proven to extend lifetime by up to 80% in laboratory aging conditions. The Smart Battery unique architecture uses a digital twin to accelerate the training of performance optimizers and predict failures. The Smart Battery technology is a new technology currently at the proof-of-concept stage.

Integration of renewable energy systems in the power system network such as wind and solar is still a challenge in our days. Energy storage systems (ESS) can overcome the disadvantage of volatile generation of the renewable energy sources. This paper presents power converters for battery energy storage systems (BESS) which can interface mediumvoltage batteries to the grid. Converter topologies comparison is performed in terms of efficiency, common mode voltage and redundancy for a 6kV series connected medium voltage batteries with a nominal power of 5MVA to act as a battery charger/discharger.