With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions about the performance of lithium-ion (Li-ion) batteries in the Boeing 787 have confirmed so far that, while battery technology is growing very quickly, developing cells with higher power and energy densities, it is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable, and cost-efficient solution. The specific characteristics and needs of the smart grid and EVs, such as deep charge/discharge protection and accurate state-of-charge (SOC) and state-of-health (SOH) estimation, intensify the need for a more efficient BMS. The BMS should contain accurate algorithms to measure and estimate the functional status of the battery and, at the same time, be equipped with state-of-the-art mechanisms to protect the battery from hazardous and inefficient operating conditions.

Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles

Battery equalization active methods

Battery health monitoring and management is of extreme importance for the performance and cost of electric vehicles. This paper is concerned with machine-learning-enabled battery state-of-health (SOH) indication and prognosis. The sample entropy of short voltage sequence is used as an effective signature of capacity loss. Advanced sparse Bayesian predictive modeling (SBPM) methodology is employed to capture the underlying correspondence between the capacity loss and sample entropy. The SBPM-based SOH monitor is compared with a polynomial model developed in our prior work. The proposed approach allows for an analytical integration of temperature effects such that an explicitly temperature-perspective SOH estimator is established, whose performance and complexity is contrasted to the support vector machine (SVM) scheme. The forecast of remaining useful life is also performed via a combination of SBPM and bootstrap sampling concepts. Large amounts of experimental data from multiple lithium-ion battery cells at three different temperatures are deployed for model construction, verification, and comparison. Such a multi-cell setting is more useful and valuable than only considering a single cell (a common scenario). This is the first known application of combined sample entropy and SBPM to battery health prognosis.

Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling

In conventional equalizers, the facts of bulky size and high cost are widespread. Particularly, the zero-switching loss and zero-voltage gap (ZVG) between cells are difficult to implement due to the high-frequency hard switching and the voltage drop across power devices. To overcome these difficulties, a direct cell-to-cell battery equalizer based on quasi-resonant LC converter (QRLCC) and boost dc-dc converter (BDDC) is proposed. The QRLCC is employed to gain zero-current switching, leading to a reduction of power losses. The BDDC is employed to enhance the equalization voltage gap for large balancing current and ZVG between cells. Moreover, through controlling the duty cycle of the BDDC, the topology can online adaptively regulate the equalization current according to the voltage difference, which not only effectively prevents overequalization but also abridges the overall balancing time. Instead of a dedicated equalizer for each cell, only one balancing converter is employed and shared by all cells, reducing the size and implementation cost. Simulation and experimental results show the proposed scheme exhibits outstanding balancing performance, and the energy conversion efficiency is higher than 98%. The validity of the proposed equalizer is further verified by a quantitative and systematic comparison with the existing active balancing methods.

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A Cell-to-Cell Battery Equalizer With Zero-Current Switching and Zero-Voltage Gap Based on Quasi-Resonant LC Converter and Boost Converter

This paper evaluates a hybrid powertrain based on fuel cell (FC), battery, and supercapacitor (SC) for the “Urbos 3” tramway, which currently operates powered by SC in the city of Zaragoza, Spain. Due to the dynamic limitations of the main energy source, a proton-exchange-membrane (PEM) FC, other energy secondary sources (ESSs), battery and SC, are needed to supply the vehicle power demand. Moreover, these energy sources allow the energy recovery during regenerative braking. The different sources are connected to a dc bus through dc-dc converters which adapt their variable voltages to the bus voltage and allow the control of energy flow between the sources and the load. The components of the hybrid tramway have been modeled in Matlab/Simulink and are based on commercially available devices. The energy management system used in this work to achieve a proper operation of the energy sources of the hybrid powertrain is based on predictive control. Simulations for the real cycle of the tramway show the suitability of the proposed powertrain and control strategy.

Predictive Control for the Energy Management of a Fuel-Cell–Battery–Supercapacitor Tramway

The battery is a fundamental component of electric vehicles, which represent a step forward towards sustainable mobility. Lithium chemistry is now acknowledged as the technology of choice for energy storage in electric vehicles. However, several research points are still open. They include the best choice of the cell materials and the development of electronic circuits and algorithms for a more effective battery utilization. This paper initially reviews the most interesting modeling approaches for predicting the battery performance and discusses the demanding requirements and standards that apply to ICs and systems for battery management. Then, a general and flexible architecture for battery management implementation and the main techniques for state-of-charge estimation and charge balancing are reported. Finally, we describe the design and implementation of an innovative BMS, which incorporates an almost fully-integrated active charge equalizer.

Batteries and battery management systems for electric vehicles

The charge stored in series-connected lithium batteries needs to be well equalized between the elements of the series. We present here an innovative lithium-battery cell-to-cell active equalizer capable of moving charge between series-connected cells using a super-capacitor as an energy tank. The system temporarily stores the charge drawn from a cell in the super-capacitor, then the charge is moved into another cell without wasting energy as it happens in passive equalization. The architecture of the system which employs a digitally-controlled switching converter is compared with the state of the art, then fully investigated, together with the methodology used in its design. The performance of the system is described by presenting and discussing the experimental results of laboratory tests. The most innovative and attractive aspect of the proposed system is its very high efficiency, which is over 90%.

High-Efficiency Digitally Controlled Charge Equalizer for Series-Connected Cells Based on Switching Converter and Super-Capacitor

This paper presents a novel approach for battery pack reconfiguration in high-power applications, where many high capacity elementary cells are series-connected to meet the power and energy requirements of the application. The novelty of the approach is that reconfiguration is applied at the module level rather than at the cell level, being a module a segment of the battery pack. A very good trade-off between reconfiguration flexibility and complexity of the implementation is achieved. A key point of the proposed architecture is the module switch, which must be able to connect or bypass a battery module by sustaining high currents without degrading the overall battery efficiency. The design of the module switch is presented, together with an implementation suitable for the battery pack of a hybrid fuel-cell small van. Experimental results show that the switch operates with continuous battery currents up to 160 A. To our knowledge, these experimental results are the first published on battery pack reconfiguration in high-power applications.

Design of a module switch for battery pack reconfiguration in high-power applications

This paper describes the design of a modular battery management system for electric off-road vehicles, where lithiumion batteries are expected to be widely used. A massive electrification of off-road vehicles can be enabled by the availability of a standard battery module, provided with an effective management unit. The design and some preliminary experimental results of the module management unit are discussed in this paper. The unit contains a high current active equalizer that enables the dynamic charge equalization among cells and maximizes the usable capacity of the battery.

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Design of the battery management system of LiFePO 4 batteries for electric off-road vehicles

An electronic meter to measure surface seawater density is presented. It is based on the measurement of the difference in displacements of a surface level probe and a weighted float, which according to Archimedes’ law depends on the density of the water. The displacements are simultaneously measured using a high-accuracy magnetostrictive sensor, to which a custom electronic board provides a wireless connection and power supply so that it can become part of a wireless sensor network. The electronics are designed so that different kinds of wireless networks can be used, by simply changing the wireless module and the relevant firmware of the microcontroller. Lastly, laboratory and at-sea tests are presented and discussed in order to highlight the functionality and the performance of a prototype of the wireless density meter node in a Bluetooth radio network. The experimental results show a good agreement of the values of the calculated density compared to reference hydrometer readings.

https://www.mdpi.com/1424-8220/12/3/2954/pdf

G. Fantechi

Papers

Batteries and battery management systems for electric vehicles

High-Efficiency Digitally Controlled Charge Equalizer for Series-Connected Cells Based on Switching Converter and Super-Capacitor

Design of a module switch for battery pack reconfiguration in high-power applications

Design of the battery management system of LiFePO 4 batteries for electric off-road vehicles

Wireless Sensor Node for Surface Seawater Density Measurements