Advanced Battery Technologies: New Applications and Management Systems

In recent years, lithium-ion batteries (LIBs) have been increasingly contributing to the development of novel engineering systems with energy storage requirements. LIBs are playing an essential role in our society, as they are being used in a wide variety of applications, ranging from consumer electronics, electric mobility, renewable energy storage, biomedical applications, or aerospace systems. Despite the remarkable achievements and applicability of LIBs, there are several features within this technology that require further research and improvements. In this book, a collection of 10 original research papers addresses some of those key features, including: battery testing methodologies, state of charge and state of health monitoring, and system-level power electronics applications. One key aspect to emphasize when it comes to this book is the multidisciplinary nature of the selected papers. The presented research was developed at university departments, institutes and organizations of different disciplines, including Electrical Engineering, Control Engineering, Computer Science or Material Science, to name a few examples. The overall result is a book that represents a coherent collection of multidisciplinary works within the prominent field of LIBs

Battery Management Systems of Electric and Hybrid Electric Vehicles

The topics of interest in this book include significant challenges in the BMS design of EV/HEV. The equivalent models developed for several types of integrated Li-ion batteries consider the environmental temperature and ageing effects. Different current profiles for testing the robustness of the Kalman filter type estimators of the battery state of charge are used in this book. Additionally, the BMS can integrate a real-time model-based sensor Fault Detection and Isolation (FDI) scheme for a Li-ion cell undergoing degradation, which uses the recursive least squares (RLS) method to estimate the equivalent circuit model (ECM) parameters. This book will fully meet the demands of a large community of readers and specialists working in the field due to its attractiveness and scientific content with a great openness to the side of practical applicability. This covers various interesting aspects, especially related to the characterization of commercial batteries, diagnosis and optimization of their performance, experimental testing and statistical analysis, thermal modelling, and implementation of the most suitable Kalman filter type estimators of high accuracy to estimate the state of charg

Dc Line-Interactive Uninterruptible Power Supply (UPS) with Load Leveling for Constant Power and Pulse Loads

Uninterruptable Power Supply (UPS) systems are usually considered as a backup power for electrical systems, providing emergency power when the main power source fails. UPS systems ensure an uninterruptible, reliable and high quality electrical power for systems with critical loads in which a continuous and reliable power supply is a vital requirement. A novel UPS system topology, DC line-interactive UPS, has been introduced. The new proposed UPS system is based on the DC concept where the power flow in the system has DC characteristic. The new DC UPS system has several advantageous with respect to the on-line 3-phase UPS which is extensively used in industry, such as lower size, cost and weight due to replacing the three-phase dual converter in the on-line UPS system with a single stage single phase DC/DC converter and thus higher efficiency is expected. The proposed system will also provide load leveling feature for the main AC/DC rectifier which has not been offered by conventional AC UPS systems. It applies load power smoothing to reduce the rating of the incoming AC line and consequently reduce the installation cost and time. Moreover, the new UPS technology improves the medical imaging system up-time, reliability, efficiency, and cost, and is applicable to several imaging modalities such as CT, MR and X-ray as well. A comprehensive investigation on different energy storage systems was conducted and couple of most promising Li-ion cell chemistries, LFP and NCA types, were chosen for further aggressive tests. A battery pack based on the LFP cells with monitoring system was developed to be used with the DC UPS testbed. The performance of the DC UPS has also been investigated. The mathematical models of the system are extracted while loaded with constant power load (CPL) and constant voltage load (CVL) during all four modes of operation. Transfer functions of required outputs versus inputs were extracted and their related stability region based on the Routh-Hurwitz stability criteria were found. The AC/DC rectifier was controlled independently due to the system configuration. Two different control techniques were proposed to control the DC/DC converter. A linear dual-loop control (DLC) scheme and a nonlinear robust control, a constant frequency sliding mode control (CFSMC) were investigated. The DLC performance was convincing, however the controller has a limited stability region due to the linearization process and negative incremental impedance characteristics of the CPL which challenges the stability of the system. A constant switching frequency SMC was also developed based on the DC UPS system and the performance of the system were presented during different operational modes. Transients during mode transfers were simulated and results were depicted. The controller performances met the control goals of the system. The voltage drop during mode transitions, was less than 2% of the rated output voltage. Finally, the experimental results were presented. The high current discharge tests on each selected Li-ion cell were performed and results presented. A testbed was developed to verify the DC UPS system concept. The test results were presented and verified the proposed concept

Modeliranje i regulacija pogona električnog vozila opremljenog hibridnim baterijsko-ultrakondenzatorskim sustavom za pohranu energije

U radu je opisana paralelna aktivna struktura baterijsko-ultrakondenzatorskih sustava za pohranu energije, te glavne značajke suvremenih litijevih baterija za automobilske primjene i visokonaponskih ultrakondenzatorskih modula za primjene u transportu. Na temelju pretpostavljene topologije DC sabirnice električnog vozila postavljen je matematički model koji uključuje podsustave baterije i ultrakondenzatora opremljene DC/DC pretvaračima snage s ugrađenim regulatorima struje, te podsustav pogonskog servomotora (sinkronog motora s permanentnim magnetima) opremljenog reguliranim DC/AC pretvaračem (izmjenjivačem). Tako dobiveni model elektromotornog pogona vozila integriran je u pojednostavljeni model dinamike vozila za pravocrtno gibanje. Na temelju izvedenog matematičkog modela električnog vozila projektirani su podređeni sustavi regulacije struje baterije, ultrakondenzatora i pogonskog servomotora, te sustav koordinacije tokova snage baterije/ultrakondenzatora prema DC sabirnici vozila, uključujući pomoćni sustav regulacije stanja napunjenosti ultrakondenzatorskog modula. Potom je projektiran i nadređeni sustave regulacije pogona vozila, a koji uključuje regulaciju napona DC sabirnice i sustav predupravljanja okretnim momentom pogonskog servomotora, te odgovarajući sustav unaprijedne kompenzacije opterećenja na DC sabirnici proporcionalnog okretnom momentu servomotora. Valjanost predloženih koncepata regulacije ispitana je simulacijama na računalu za slučaj pokretanja vozila iz mirovanja zadavanjem komande konstantne akceleracije, te za profile brzine vozila tipičnih za vožnju u urbanim uvjetima (NEDC vozni ciklus)

Online modelling and state-of-charge estimation for lithium-titanate battery

Superior safety, is a promising energy storage element for electric vehicles. Its features can be fully utilised by using a fast charger and a high performance battery management system. Battery model is vital to a battery charger design for characterising the charging behaviours of a battery. Additionally, a robust state-ofcharge (SoC) estimation should be realised for a reliable battery management. This thesis develops a battery model for charger design and a robust method for SoC estimation by using MATLAB. The thesis proposed a transfer function-based battery model which is applicable for small-signal analysis and large-signal simulation of battery charger design, in order to capture the charging profiles of LTO battery. Busse’s adaptive rule, which has simple computations, is applied to improve the accuracy of Kalman filter-based SoC estimation. Busse’s adaptive Kalman filters are also applied for SoC estimation with online battery modelling to eliminate the complicated process of battery modelling. This study was conducted by using 2.4 V, 15 Ah LTO batteries. The batteries were tested with continuous current test and pulsed current test at several ambient temperatures (-25 ºC, 0 ºC, 25 ºC and 50 ºC) and charge/discharge currents (0.5 C, 1 C, 2 C). Additionally, modified dynamic stress tests at several temperatures (-15 ºC, 0 ºC, 15 ºC, 25 ºC, 35 ºC and 50 ºC) were also performed to test the battery under real EV environment. Results of the battery modelling showed that the developed transfer function-based battery model is accurate where the root-mean-square modelling error is less than 30 mV. The results also revealed that the Busse’s adaptive rule has effectively improved the Kalman filter-based SoC estimation for the case of offline battery model by giving a higher accuracy and shorter convergence time. Additionally, Busse’s adaptive Extended Kalman Filter gave a better accuracy in SoC estimation with online battery modelling. The proposed transfer function-based battery model provides a helpful solution for the battery charger design while the proposed Busse’s adaptive Kalman filter offers an accurate and robust SoC estimation for both offline and online battery models

Design and validation of a battery management system for solar-assisted electric vehicles

Expanding the travel mileage of power batteries is of great significance for electric vehicles (EVs). The solar battery pack is considered as a promising supplement to the battery management system (BMS) of EVs but integrating solar power into EVs remains a challenge. This paper proposes a BMS that coordinates the solar panels and the lithium battery system. The proposed BMS mainly involves three aspects. Firstly, an equivalent second-order resistance-capacitance model is established and afterwards is identified by using an improved recursive least squares algorithm. Then, the maximum power prediction strategy is developed based on the advanced state of charge (SOC) algorithm and the available solar energy estimation algorithm. Thirdly, a multi-stage constant current charging strategy based on the adaptive genetic algorithm is designed to optimize the battery temperature rise and charging time simultaneously. The proposed BMS is validated by the experiment on a real-world solar-assisted EV. The results indicate that the proposed power prediction strategy can accurately estimate the available power for EVs. Compared with the widely-used charging method, the developed optimal charging strategy reduces the charging time and temperature rise by 7%–11% and 36%–45%, respectively

A novel adaptive state of charge estimation method of full life cycling lithium-ion batteries based on the multiple parameter optimization.

The state of charge (SoC) estimation is the safety management basis of the packing lithium-ion batteries (LIB), and there is no effective solution yet. An improved splice equivalent modeling method is proposed to describe its working characteristics by using the state-space description, in which the optimization strategy of the circuit structure is studied by using the aspects of equivalent mode, analog calculation, and component distribution adjustment, revealing the mathematical expression mechanism of different structural characteristics. A novel particle adaptive unscented Kalman filtering algorithm is introduced for the iterative calculation to explore the working state characterization mechanism of the packing LIB, in which the incorporate multiple information is considered and applied. The adaptive regulation is obtained by exploring the feature extraction and optimal representation, according to which the accurate SoC estimation model is constructed. The state of balance evaluation theory is explored, and the multiparameter correction strategy is carried out along with the experimental working characteristic analysis under complex conditions, according to which the optimization method is obtained for the SoC estimation model structure. When the remaining energy varies from 10% to 100%, the tracking voltage error is less than 0.035 V and the SoC estimation accuracy is 98.56%. The adaptive working state estimation is realized accurately, which lays a key breakthrough foundation for the safety management of the LIB packs

Control of Lithium-Ion Battery Warm-up from Sub-zero Temperatures

The archetype of rechargeable technology, Li-ion batteries have over the last decade benefited from improvements in material science through increased energy and power density. Although widely adopted, these batteries suffer from significant performance degradation at low temperatures, posing a challenge for automotive applications, especially during vehicle start-up. This begs the question: if one was to seek an energy optimal warm-up strategy, how would it look? Moreover, if as much as 22% of reduction in range of electric vehicles is attributable to onboard battery heating systems, would an optimal heating strategy alleviate this energy drain and at what drawback? This thesis addresses these questions. To that end, we pose and solve two energy-optimal warm-up strategies in addition to developing tools that will enable one to make prudent decisions on whether warm-up is feasible if the battery energy state falls too low. In this dissertation, we address the four main aspects of control design modeling, control, verification and adaptation. There are two primary control strategies that are designed in this dissertation and tools to analyze them are developed. The first warm-up scenario involves a receding horizon optimal control problem whose objective trades-offs increase in battery's temperature by self-heating against energy expended. The shape of battery current is restricted to be bi-directional pulses that charge and discharge the cell at relatively high frequencies via an external capacitor. The optimal control problem solves for the amplitude of the pulse train and the results clarify issues associated with capacitor size, time and lost energy stored. The second control policy is deduced by solving an optimal discharge control problem for the trajectory of power that could self-heat the cell and at the same time feed an external heater whilst minimizing the loss in state of charge. Batteries inevitably age as they are used and consequently their dynamics also change. Since both proposed methods are model based, the last of part of this dissertation proposes a novel augmented-state-space partitioning technique which can be used to design cascaded nonlinear estimators. Using this partitioning technique, the relative average estimability of the different states of the electrical and thermal model is studied and Dual Extended Kalman Filters are built and validated in simulations. All the methods developed are demonstrated via a combination of simulation and experiments on Iron Phosphate or Nickel Manganese Cobalt Li-ion battery cell which have high power capability and could be used in replacement of 12V starter batteries or 48V start-stop applications.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136964/1/elemsn_1.pd