Enhanced electrical model of Lithium-based batteries accounting the charge redistribution effect

Within the context of the electrical circuit modeling of batteries, this paper proposes an improvement of the most common electric equivalent circuit used for Lithium cells. The main improvement is based on the modeling of the so-called charge redistribution phenomenon that characterizes the dynamic voltage during charging/discharging and relaxation phases. In particular, the aim of the paper is to prove that the model recently proposed by the Authors to represent the same phenomenon in supercapacitors, can be extended also to Lithium batteries. The proposed model is validated by means of experimental results carried out on a 30 Ah 2.3 V Lithium-Titanate cell with reference to different charge/discharge cycles

A systematic approach to the impedance of surface layers with mixed conductivity forming on electrodes

Electrode impedance can be evaluated on the basis of the electrode reaction kinetics in many systems, even for complicated electrode reactions. However, when a surface layer is present on the electrode surface, the theoretically well-established impedance model of the electrode reaction is often completed with phenomenological equivalent circuit elements in order to achieve the number of time constants as derived from the electrode impedance spectra measured In these cases, the meaning of the phenomenological equivalent circuit elements are often unclear, though the presence of these elements is helpful to describe the system throughout the frequency domain used for the measurement. In the present work, an attempt will be shown to separate the effect of the electronic and ionic charge transfer in a surface layer and to identify the appropriate equivalent circuits. Examples are shown from the fields of lithium-ion batteries where a solid electrolyte interface as a surface layer is present at the negative electrode and the contribution of various charge carriers may be of importance

Evaluation of rapid electric battery charging techniques

Battery powered electric vehicles are gaining popularity worldwide. This is trend is driven by several factors including the need to reduce air and noise pollution, and dependence on fossil fuels. The main drawback of today\u27s electric vehicle is its limited range, and the long time duration that is required to charge the electric batteries. This thesis addresses the latter problem. In recent years, significant progress (through research and development) has been made to accelerate the charging time of the electric vehicle batteries through pulse charging rather than supplying continuous current and/or voltage. Some patented fast charging techniques demonstrated reduced charging times from 8 hours down to 45 minutes, and the current goal is to reduce this to the 10-minute range. This thesis will evaluate the published fast charging techniques in terms of their efficiency, accuracy of state of charge, threat of overcharge and impact of life cycle. The merits of the various battery interrogation techniques will be analyzed through modeling and computer simulation

Advanced Control of Active Distribution Networks Integrating Dispersed Energy Storage Systems

Due to the increased penetration of Distributed Generations (DGs) in distribution networks, the system control and operation may become quite different from the case of traditional network. Most DGs can only provide intermittent power to the Active Distribution Networks (ADNs) due to the intermittent nature of the resources. Moreover, ADN utilities usually do not own DGs, and have difficulty in controlling directly DGs output powers. The main problem related to the considerable connection of DGs is usually associated to the node voltage quality and line congestion mitigation. Within the above context, the motivating factors for this thesis are supported by the issues related to optimal operation and control of ADNs integrating stochastic and non-stochastic DGs. One of the most promising near-term solution is offered by using distributed Energy Storage Systems (ESSs) which can perform their full role to guarantee a more flexible network. Indeed, the availability of ESSs allows, in principle, to: (i) actively control the power flows into the grid, (ii) indirectly control the voltage profiles along the network feeders and (iii) locally balance the hour/daily and weekly load variations. In this thesis, ESSs are assumed to be the only controllable devices in ADNs. As a result, DGs can be indirectly controlled by means of ESSs. First, this manuscript presents control-oriented model for ESSs. In this respect, the accurate estimation of ESS behavior is utmost important. A generic charge representative model for any ESSs is proposed. Moreover, an improvement of the most common electric equivalent circuit models for the two selected ESSs with different characteristics (namely supercapacitors and batteries) is provided for the development of specific control schemes. They are based on the modeling of redistribution of charges that characterizes the dynamic behaviors of the two devices during long time charging/discharging and relaxation phases. Second, this manuscript presents advanced control/scheduling algorithm for ADNs. The operation and control of ADNs can be achieved either centrally or in a decentralized way. The amount of information to be centrally treated would considerably grow due to the number of generation equipmentâs inserted into the grid and the stochastic operation nature of some of them. This consideration introduces the idea that some ADN operation problems, such as voltage control or line congestion mitigation, can be solved in a distributed manner which would help to relieve the information processing burden and to enhance the system security while preventing unwanted event from propagating through the grid. Therefore, the decentralized schemes are considered subdividing the network into quasi-autonomous areas. To this end, given a set of ESSs optimally located in a balanced and radial ADN, this thesis proposes a network partitioning strategy for the optimal voltage control of ADNs. Thus, the network is decomposed into several areas; each under the control of one ESS which has maximum influence on its corresponding area. Based on this clustering, decentralized scheduling strategies and real-time decentralized control algorithms for the clustered ADNs are proposed. The proposed zonal control capability focuses on voltage control and line congestion management. In both proposed decentralized scheduling and real-time control algorithms the communication among different areas is defined using the concept of Multi-Agent Systems

Grid congestion mitigation and battery degradation minimisation using model predictive control in PV-based microgrid

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksIncreasing integration of photovoltaic (PV) system in electric grids cause congestion during peak power feed-in. Battery storage in PV systems increases self-consumption, for consumer's benefit. However with conventional maximising self consumption (MSC) control for battery scheduling, the issue of grid congestion is not addressed. The batteries tend to be fully charged early in the day and peak power is still fed-in to grid. This also increases battery degradation due to increased dwell time at high state of charge (SOC) levels. To address this issue, this work uses a model predictive control (MPC) for scheduling in PV system with battery storage to achieve multiple objectives of minimising battery degradation, grid congestion, while maximising self consumption. In order to demonstrate the improvement, this work compares the performances of MPC and MSC schemes when used in battery scheduling. The improvement is quantified through performance indices like self consumption ratio, peak power reduction and battery capacity fade for one-year operation. An analysis on computation burden and maximum deterioration in MPC performance under prediction error is also carried out. It is concluded that, compared to MSC, MPC achieves similar self consumption in PV systems while also reducing grid congestion and battery degradation.Peer ReviewedPostprint (author's final draft

A novel safety assurance method based on the compound equivalent modeling and iterate reduce particle‐adaptive Kalman filtering for the unmanned aerial vehicle lithium ion batteries.

The safety assurance is very important for the unmanned aerial vehicle lithium ion batteries, in which the state of charge estimation is the basis of its energy management and safety protection. A new equivalent modeling method is proposed for the mathematical expression of different structural characteristics, and an improved reduce particle-adaptive Kalman filtering model is designed and built, in which the incorporate multiple featured information is absorbed to explore the optimal representation by abandoning the redundant and abnormal information. And then, the multiple parameter identification is investigated that has the ability of adapting the current varying conditions, according to which the hybrid pulse power characterization test is accommodated. As can be known from the experimental results, the polynomial fitting treatment is carried out by conducting the curve fitting treatment and the maximum estimation error of the closed-circuit-voltage is 0.48% and its state of charge estimation error is lower than 0.30% in the hybrid pulse power characterization test, which is also within 2.00% under complex current varying working conditions. The iterate calculation process is conducted for the unmanned aerial vehicle lithium ion batteries together with the compound equivalent modeling, realizing its adaptive power state estimation and safety protection effectively

Wood-derived lignin-based fibers as supercapacitor electrodes

Today, in order to replace fossil energy sources with renewable energy sources such as solar and wind, reliable energy storage systems that can provide power regardless of the intermittent nature of the energy sources must be created. Especially with the future’s rising energy demands the development of such energy storage systems from green-collar materials with the least negative environmental impact is pressing. Transforming the major cheap and replenishable forest resource, wood, to carbon materials with desirable morphologies can potentially be used as supercapacitors (SC) electrodes with long cycle life and higher power density than batteries today. Forest materials are abundant, but their extraction to manufacturing hold practicality issues due to yet not established procedures. Active research has focused on advancing lignin-based electrospun carbon fibers (ELCFs) and activated carbons with simple, high-yielding mass production units. The ECLF is self-standing and flexible, making them a prospective candidate for flexible and wearable electronics. As of today, the materials face shortcomings such as low electrical conductivity and poor mechanical stability post thermal carbonization especially if the spinning discards fossil based secondary polymers. Research on optimized fractionated high molecular weight lignin solutions from black liquor - an industrial paper and pulp industry byproduct - have improved their spinnability. Turning these lignin-based materials to commercial utilization requires more investigation and understanding of the materials.This thesis discusses the electrochemical performance of lignin fibers as highly reliable supercapacitor electrode material. Grafting the right amount of beneficial functional groups on the ELCF surface by low-power oxygen plasma treatment, the properties of the electrode-electrolyte interface significantly improved the wettability, increased active sites favorable for pseudocapacitance, reduced diffusion limitation, thus enhancing its electrochemical storage ability. Quite often, the surface functional groups have a detrimental impact on a device’s electrochemical performance such as increased resistance, low power performance, low stability, and high self-discharge rate. However, the non-invasive nature of the conducted plasma treatment made a remarkable improvement in the capacitive performance in KOH aqueous medium without compromising power and energy performance metrics. Preliminary quantification performed to understand the charge storage behavior in other aqueous electrolytes H2SO4 and Li2SO4 are also revealed. Furthermore, the observation of enhanced electrochemical performance via applying a voltage of 1.2 V and 10 000 charge-discharge cycles is discussed. With the competition of supercapacitors energy storage ability with batteries, efforts have been taken to make thick electrodes to boost energy density. Electrodes with high areal mass loading in supercapacitor maximize the packing density of the electroactive electrode materials while lowering the manufacturing cost by reducing the number of inactive material layers. Herein, the fabrication and electrochemical performance of 180-280 μm thick activated carbon (AC) electrodes with 2 wt% of hair-like carbonized lignin carbon fibers (LCF) as conductive agent alongside carbon black in the electrode matrix was assessed. In the resulting electrodes, the LCF inclusions into the AC matrix increased flexibility and contributed to improved capacitances due to better conductivity in the electrodes. The reduced resistances suggest that LCFs act as an intermediate layer among AC particles and serve as conductive pathways, facilitating electronic conductivity of more AC particles in deeper layers. Considering the biologically hazardous nature of other commonly used binders like polytetrafluoroethylene, and polyvinylidene fluoride, environmentally friendly binder microfibrillated cellulose (MFC) binder was successfully used to fabricate freestanding electrodes

Adaptive iterative working state prediction based on the double unscented transformation and dynamic functioning for unmanned aerial vehicle lithium-ion batteries.

In lithium-ion batteries, the accuracy of estimation of the state of charge is a core parameter which will determine the power control accuracy and management reliability of the energy storage systems. When using unscented Kalman filtering to estimate the charge of lithium-ion batteries, if the pulse current change rate is too high, the tracking effects of algorithms will not be optimal, with high estimation errors. In this study, the unscented Kalman filtering algorithm is improved to solve the above problems and boost the Kalman gain with dynamic function modules, so as to improve system stability. The closed-circuit voltage of the system is predicted with two non-linear transformations, so as to improve the accuracy of the system. Meanwhile, an adaptive algorithm is developed to predict and correct the system noises and observation noises, thus enhancing the robustness of the system. Experiments show that the maximum estimation error of the second-order Circuit Model is controlled to less than 0.20V. Under various simulation conditions and interference factors, the estimation error of the unscented Kalman filtering is as high as 2%, but that of the improved Kalman filtering algorithm are kept well under 1.00%, with the errors reduced by 0.80%, therefore laying a sound foundation for the follow-up research on the battery management system

Comparison of one and two time constant models for lithium ion battery

The fast and accurate modeling topologies are very much essential for power train electrification. The importance of thermal effect is very important in any electrochemical systems and must be considered in battery models because temperature factor has highest importance in transport phenomena and chemical kinetics. The dynamic performance of the lithium ion battery is discussed here and a suitable electrical equivalent circuit is developed to study its response for sudden changes in the output. An effective lithium cell simulation model with thermal dependence is presented in this paper. One series resistor, one voltage source and a single RC block form the proposed equivalent circuit model. The 1 RC and 2 RC Lithium ion battery models are commonly used in the literature are studied and compared. The simulation of Lithium-ion battery 1RC and 2 RC Models are performed by using Matlab/Simulink Software. The simulation results in his paper shows that Lithium-ion battery 1 RC model has more maximum output error of 0.42% than 2 RC Lithium-ion battery model in constant current condition and the maximum output error of 1 RC Lithium-ion battery model is 0.18% more than 2 RC Lithium-ion battery model in UDDS Cycle condition. The simulation results also show that in both simple and complex discharging modes, the error in output is much improved in 2 RC lithium ion battery model when compared to 1 RC Lithium-ion battery model. Thus the paper shows for general applications like in portable electronic design like laptops, Lithium-ion battery 1 RC model is the preferred choice and for automotive and space design applications, Lithium-ion 2 RC model is the preferred choice. In this paper, these simulation results for 1 RC and 2 RC Lithium-ion battery models will be very much useful in the application of practical Lithium-ion battery management systems for electric vehicle applications