Identifiability and parameter estimation of the single particle lithium-ion battery model

This paper investigates the identifiability and estimation of the parameters of the single particle model (SPM) for lithium-ion battery simulation. Identifiability is addressed both in principle and in practice. The approach begins by grouping parameters and partially non-dimensionalising the SPM to determine the maximum expected degrees of freedom in the problem. We discover that, excluding open circuit voltage, there are only six independent parameters. We then examine the structural identifiability by considering whether the transfer function of the linearised SPM is unique. It is found that the model is unique provided that the electrode open circuit voltage functions have a known non-zero gradient, the parameters are ordered, and the electrode kinetics are lumped into a single charge transfer resistance parameter. We then demonstrate the practical estimation of model parameters from measured frequency-domain experimental electrochemical impedance spectroscopy (EIS) data, and show additionally that the parametrised model provides good predictive capabilities in the time domain, exhibiting a maximum voltage error of 20 mV between model and experiment over a 10 minute dynamic discharge.Comment: 16 pages, 9 figures, pre-print submitted to the IEEE Transactions on Control Systems Technolog

Battery Modeling and Parameter Extraction for Drive Cycle Loss Evaluation of a Modular Battery System for Vehicles Based on a Cascaded H-Bridge Multilevel Inverter

This article deals with the modeling and the parameterization of the battery packs used in cascaded H-bridge multilevel propulsion inverters. Since the battery packs are intermittently conducting the motor currents, the battery cells are stressed with a dynamic current containing a substantial amount of low-order harmonic components up to a couple of kHz, which is a major difference in comparison to a traditional two-level inverter drive. Different models, such as pure resistive and dynamic RC -networks, are considered to model the energy losses for different operating points (OPs) and driving cycles. Using a small-scale setup, the models’ parameters are extracted using both a low-frequency, pulsed current, and an electrochemical impedance spectroscopy (EIS) sweep. The models are compared against measurements conducted on the small-scale setup at different OPs. Additionally, a drive cycle loss comparison is simulated. The simple resistive model overestimates the losses by about 20% and is, thus, not suitable. The dynamic three-time-constant model, parameterized by a pulsed current, complies with the measurements for all analyzed OPs, especially at low speed, with a maximum deviation of 3.8%. Extracting the parameters using an EIS seems suitable for higher speeds, though the losses for the chosen OPs are underestimated by 1.5%–7.9%

A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors

Electrochemical energy storage systems play an important role in diverse applications, such as electrified transportation and integration of renewable energy with the electrical grid. To facilitate model-based management for extracting full system potentials, proper mathematical models are imperative. Due to extra degrees of freedom brought by differentiation derivatives, fractional-order models may be able to better describe the dynamic behaviors of electrochemical systems. This paper provides a critical overview of fractional-order techniques for managing lithium-ion batteries, lead-acid batteries, and supercapacitors. Starting with the basic concepts and technical tools from fractional-order calculus, the modeling principles for these energy systems are presented by identifying disperse dynamic processes and using electrochemical impedance spectroscopy. Available battery/supercapacitor models are comprehensively reviewed, and the advantages of fractional types are discussed. Two case studies demonstrate the accuracy and computational efficiency of fractional-order models. These models offer 15–30% higher accuracy than their integer-order analogues, but have reasonable complexity. Consequently, fractional-order models can be good candidates for the development of advanced b attery/supercapacitor management systems. Finally, the main technical challenges facing electrochemical energy storage system modeling, state estimation, and control in the fractional-order domain, as well as future research directions, are highlighted

Elektrochemische Impedanzspektroskopie an alternden Lithium-Ionen Batterien

The change of Lithium-ion Battery (LiB) model parameters during cyclic ageing is analysed in order to relate it to the capacity of the cell. Therefore, approaches to distinguish between anode and cathode contributions to the full cell impedance spectrum are developed. The results from a new measurement routine, using temperature gradients across a full cell, show that a successful assignment of the charge transfer processes at the cathode and anode is possible. For the analysed cell the cathode charge transfer processes occur at a lower time constant than the related anode processes. With the information of such an assignment, ageing of a 30 mAh pouch cell is analysed with Electrochemical Impedance Spectroscopy (EIS). A Newman-type LiB-model for this cell is extended by a physical ageing model including a Solid Electrolyte Iterphase (SEI), loss of active surface area and loss of active material. The simulation results of this model in combination with the related measurement results are used with a parameter identification algorithm to quantify the thickness of the SEI, the amount of isolated surface area and the loss of active material. The results show that the impedance increase is caused by a decrease of active surface area while the capacity decrease is caused by a loss of active material at the anode and cathode. The SEI thickness has found to increase to 45 nm while the active surface areas of the anode and cathode decrease by 20% and 57% respectively until the End Of Life (EOL) of the cell after 400 cycles. The change of the ageing parameters occurs in correlation to the decrease of the capacity of the analysed cell. Finally, the identifiability of kinetic, transport and ageing parameters, identified using this approach, has been quantified using Fisher-Information-Matrices (FIMs) showing that the impedance spectra are sensitive enough to the ageing parameters to ensure their precise identifiability.Die Veränderung von Parametern eines Lithium-Ionen Batteriemodels während zyklischer Alterung wird analysiert, um Rückschlüsse auf die Kapazität der Zelle zu ziehen. Hierfür werden Ansätze vorgestellt, die es ermöglichen zwischen den Beiträgen von Anode und Kathode zur Vollzellimpedanz zu unterscheiden. Die Ergebnisse einer neuen Messroutine, bei der ein Temperaturgradient auf die Vollzelle aufgeprägt wird, zeigen, dass eine erfolgreiche Zuordnung der Ladungstransferprozesse an Anode und Kathode möglich ist. Für die untersuchte Zelle finden die Ladungstransferprozesse an der Kathode mit einer kleineren Zeitkonstante statt als die entsprechenden Prozesse an der Anode. Mit der Information einer solchen Zuordnung wird die Alterung einer 30 mAh Pouchzelle mit der Elektrochemischen Impedanz Spektroskopie (EIS) analysiert. Hierfür wird ein Newman-Model einer LiB um ein physikalisches Alterungsmodel erweitert, das eine Solid Electrolyte Interphase (SEI), den Verlust von aktiver Oberfläche und den Verlust von Aktivmaterial enthält. Die Ergebnisse zeigen, dass der Impedanzanstieg durch einen Verlust an aktiver Oberfläche und der Kapazitätsverlust durch einen Verlust an Aktivmaterial in Anode und Kathode verursacht wird. Bis zum Ende der Lebensdauer der Batterie nach 400 Zyklen, erhöht sich die Dicke der SEI auf 45 nm, während die aktiven Oberflächen von Anode und Kathode um 20% und 57% abnehmen. Die Veränderung der Alterungsparameter ist bei der untersuchten Zelle mit der Abnahme der Zellkapazität korreliert. Abschließend wurde die Identifizierbarkeit von kinetischen-, Transport- und Alterungsparametern mathematisch mit Fischerinformationsmatrizen untersucht undgezeigt, dass die Impedanzspektren sensitiv genug auf eine Änderung der Alterungsparameter reagieren, um diese präzise zu identifizieren

A Study of Computationally Efficient Advanced Battery Management: Modeling, Identification, Estimation and Control

Lithium-ion batteries (LiBs) are a revolutionary technology for energy storage. They have become a dominant power source for consumer electronics and are rapidly penetrating into the sectors of electrified transportation and renewable energies, due to the high energy/power density, long cycle life and low memory effect. With continuously falling prices, they will become more popular in foreseeable future. LiBs demonstrate complex dynamic behaviors and are vulnerable to a number of operating problems including overcharging, overdischarging and thermal runaway. Hence, battery management systems (BMSs) are needed in practice to extract full potential from them and ensure their operational safety. Recent years have witnessed a growing amount of research on BMSs, which usually involves topics such as dynamic modeling, parameter identification, state estimation, cell balancing, optimal charging, thermal management, and fault detection. A common challenge for them is computational efficiency since BMSs typically run on embedded systems with limited computing and memory capabilities. Inspired by the challenge, this dissertation aims to address a series of problems towards advancing BMSs with low computational complexity but still high performance. Specifically, the efforts will focus on novel battery modeling and parameter identification (Chapters 2 and 3), highly efficient optimal charging control (Chapter 4) and spatio-temporal temperature estimation of LiB packs (Chapter 5). The developed new LiB models and algorithms can hopefully find use in future LiB systems to improve their performance, while offering insights into some key challenges in the field of BMSs. The research will also entail the development of some fundamental technical approaches concerning parameter identification, model predictive control and state estimation, which have a prospect of being applied to dynamic systems in various other problem domains

Battery Management and Battery Modeling Considerations for Application in a Neighborhood Electric Vehicle

Transitioning from internal combustion engine vehicles (ICEVs) to electric vehicles (EVs) consolidates and relocates emissions, endeavoring to improve air quality, particularly in high traffic urban areas. Unfortunately, many obstacles to widespread EV use remain, broadly related to user familiarity, convenience, and effectiveness. However, EVs are better suited for some opportunities. Following the introduction, this thesis covers the process of upgrading a neighborhood electric vehicle (NEV) from lead-acid batteries to a swappable battery pack consisting of lithium iron phosphate (LiFePO4), or LFP, cells. Although LFP cells are considered safer than other lithium-ion cells, a new battery charger and battery management system (BMS) were installed to ensure proper function and maintenance. While the new electronics appeared to be successfully integrated during initial testing, several cells within the battery pack were over-discharged—or underwent voltage reversal—while outside during winter. Thus, prompted a reassessment of battery management practices and implementation, resulting in the construction of a new battery pack and redesign of the charge and discharge controls. The ensuing chapter pertains to battery management practices employed in the vehicle—and battery management in general. This chapter begins with background, wherein discusses fundamentals of cell function, modes of failure, and lastly, methods of obviating failure and protracting cell longevity. Finally, chapter four describes battery modeling from the perspective of a tool to maintain cells in EVs. Determination of immeasurable states that are important to battery management and consumer comfort are deliberated. Mathematical models and equivalent circuit models of cell behavior are of particular interest. Common equivalent circuit models are parameterized for several cells and voltage estimation capabilities are compared

In situ control of graphene oxide dispersions with a small impedance sensor

Abstract Carbon-based nanomaterials (CBNs), such as graphene and carbon nanotubes, display advanced physical and chemical properties, which has led to their widespread applications. One of these applications includes the incorporation of CBNs into cementitious materials in the form of aqueous dispersions. The main issue that arises in this context is that currently no established protocol exists as far as characterizing the dispersions. In the present article, an innovative method for quick evaluation and quantification of graphene oxide (GO) dispersions is proposed. The proposed method is electrical impedance spectroscopy (EIS) with an impedance sensor. The novelty lies on the exploitation of a small sensor for on-site (field) direct dielectric measurements with the application of alternating current. Five different concentrations of GO dispersions were studied by applying EIS and for various accumulated ultrasonic energies. The low GO concentration leads to high impedance values due to low formed current network. Two opposing mechanisms were revealed during the accumulation of ultrasonic energy, that are taking place simultaneously: breakage of the agglomerates that facilitates the flow of the electric current due to the formation of a better dispersed network, nevertheless the surface hydrophilic structure of the GO is damaged with the high accumulated ultrasonic energy. The dielectric measurements were exploited to express an appropriate quantitative ‘quality index’ to facilitate with the dispersion control of the nanostructures. An intermediate concentration of GO is suggested (about 0.15 wt% of the binder materials) to be optimal for the specific engineering application, ultrasonicated at approximately 30 to 65 kJ. The investigated methodology is highly novel and displays a high potential to be applied in-field applications where CBNs must be incorporated in building materials