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Electrochemical batteries used in energy storage systems provide a significant contribution to the development of smart grids and green transportation. In recent years, intensive research activities have been oriented to the optimal management of energy storage systems for power electronics applications in fast growing industrial sectors as EVs and HEVs. The accurate modeling of electrochemical batteries is fundamental in the design of control algorithms applied to energy storage systems. Focusing on automotive applications, in this paper a comprehensive analysis of ESS models based on equivalent electric circuits using a multi-criteria approach is presented. An extensive experimental validation has been carried out to evaluate the performance of battery models in automotive applications. [ABSTRACT FROM AUTHOR]

To obtain a full exploitation of battery potential in energy storage applications, an accurate modeling of electrochemical batteries is needed. In real terms, an accurate knowledge of state of charge (SOC) and state of health (SOH) of the battery pack is needed to allow a precise design of the control algorithms for energy storage systems (ESSs). Initially, a review of effective methods for SOC and SOH assessment has been performed with the aim to analyze pros and cons of standard methods. Then, as the tradeoff between accuracy and complexity of the model is the major concern, a novel technique for SOC and SOH estimation has been proposed. It is based on the development of a battery circuit model and on a procedure for setting the model parameters. Such a procedure performs a real-time comparison between measured and calculated values of the battery voltage while a PI-based observer is used to provide the SOC and SOH actual values. This ensures a good accuracy in a wide range of operating conditions. Moreover, a simple start-up identification process is required based on battery data-sheet exploitation. Because of the low computational burden of the whole algorithm, it can be easily implemented in low-cost control units. An experimental comparison between SOC and SOH estimation performed by suggested and standard methods is able to confirm the consistency of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper deals with the study and implementation of a losses minimization control strategy for an integrated multidrive (IMD) topology used in the drivetrain of parallel hybrid electric vehicles. In this IMD, the stator sections of a multiwinding induction machine are interfaced to the storage units through standard three-phase inverters. The goal of this study is to optimize the management of multidirectional power flows in an IMD configuration, reducing both the power losses of the induction machine and the energy storage units while keeping the computational complexity suitably low. To this aim, the proposed approach consists in a control strategy that continuously searches for the best compromise between the torque response and the power capability of each storage unit while minimizing the overall power losses. Using such an approach, a significant improvement in the overall efficiency is obtained. Simulations and experimental tests confirm the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Recent developments in fields such as portable devices, electric and hybrid vehicles and renewable energy harvesting are the main reasons why the energy storages/batteries are an object of intense research. Lead-acid batteries still play a key role, and it is old known technology. Other battery chemistries having higher power are still too much expensive for small and medium energy storages for smart grid. To achieve an effective exploitation of battery packs, it is important to have a robust and reliable battery management. Accurate state of charge estimation in battery management is a critical part. To achieve the economical and suitable energy performance including life-time extension battery nonlinearities must be considered. Analysis and comparison of widely used SOC estimation methods including Coulomb counting and Kalman filter with various battery models is the goal of the paper. Internal parameters dependencies on SOC were added to battery models used by Kalman filter to achieve high accuracy. SOC methods are verified by using two different discharge/charge tests. [ABSTRACT FROM AUTHOR]

A three-phase multi-level multi-input power converter topology is presented for grid-connected applications. It encompasses a three-phase transformer that is operated on the primary side in an open-end winding configuration. Thus, the primary winding is supplied on one side by a three-phase N-level neutral point clamped inverter and, on the other side, by an auxiliary two-level inverter. A key feature of the proposed approach is that the N-level inverter is able to perform independent management of N − 1 input power sources, thus avoiding the need for additional dc/dc power converters in hybrid multi-source systems. Moreover, it can manage an energy storage system connected to the dc-bus of the two-level inverter. The N-level inverter operates at a low switching frequency and can be equipped with very low on-state voltage drop Insulated-Gate Bipolar Transistor (IGBT) devices, while the auxiliary inverter is instead operated at low voltage according to a conventional high-frequency two-level Pulse Width Modulation (PWM) technique and can be equipped with very low on-state resistance Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) devices. Simulations and experimental results confirm the effectiveness of the proposed approach and its good performance in terms of grid current harmonic content and overall efficiency. [ABSTRACT FROM AUTHOR]