Accurate electrical battery model capable of predicting runtime and I-V performance
TL;DR: An accurate, intuitive, and comprehensive electrical battery model is proposed and implemented in a Cadence environment that accounts for all dynamic characteristics of the battery, from nonlinear open-circuit voltage, current-, temperature-, cycle number-, and storage time-dependent capacity to transient response.
Abstract: Low power dissipation and maximum battery runtime are crucial in portable electronics. With accurate and efficient circuit and battery models in hand, circuit designers can predict and optimize battery runtime and circuit performance. In this paper, an accurate, intuitive, and comprehensive electrical battery model is proposed and implemented in a Cadence environment. This model accounts for all dynamic characteristics of the battery, from nonlinear open-circuit voltage, current-, temperature-, cycle number-, and storage time-dependent capacity to transient response. A simplified model neglecting the effects of self-discharge, cycle number, and temperature, which are nonconsequential in low-power Li-ion-supplied applications, is validated with experimental data on NiMH and polymer Li-ion batteries. Less than 0.4% runtime error and 30-mV maximum error voltage show that the proposed model predicts both the battery runtime and I-V performance accurately. The model can also be easily extended to other battery and power sourcing technologies.
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TL;DR: In this article, a comprehensive review of the battery state of charge estimation and its management system for the sustainable future electric vehicles (EVs) applications is presented, which can guarantee a reliable and safe operation and assess the battery SOC.
Abstract: Due to increasing concerns about global warming, greenhouse gas emissions, and the depletion of fossil fuels, the electric vehicles (EVs) receive massive popularity due to their performances and efficiencies in recent decades. EVs have already been widely accepted in the automotive industries considering the most promising replacements in reducing CO2 emissions and global environmental issues. Lithium-ion batteries have attained huge attention in EVs application due to their lucrative features such as lightweight, fast charging, high energy density, low self-discharge and long lifespan. This paper comprehensively reviews the lithium-ion battery state of charge (SOC) estimation and its management system towards the sustainable future EV applications. The significance of battery management system (BMS) employing lithium-ion batteries is presented, which can guarantee a reliable and safe operation and assess the battery SOC. The review identifies that the SOC is a crucial parameter as it signifies the remaining available energy in a battery that provides an idea about charging/discharging strategies and protect the battery from overcharging/over discharging. It is also observed that the SOC of the existing lithium-ion batteries have a good contribution to run the EVs safely and efficiently with their charging/discharging capabilities. However, they still have some challenges due to their complex electro-chemical reactions, performance degradation and lack of accuracy towards the enhancement of battery performance and life. The classification of the estimation methodologies to estimate SOC focusing with the estimation model/algorithm, benefits, drawbacks and estimation error are extensively reviewed. The review highlights many factors and challenges with possible recommendations for the development of BMS and estimation of SOC in next-generation EV applications. All the highlighted insights of this review will widen the increasing efforts towards the development of the advanced SOC estimation method and energy management system of lithium-ion battery for the future high-tech EV applications.
1,150 citations
TL;DR: In this paper, a battery management system (BMS) for the smart grid and electric vehicles (EVs) has been proposed to improve the performance of Li-ion batteries.
Abstract: 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.
721 citations
Cites background from "Accurate electrical battery model c..."
...It is proposed to use two RC pairs to represent both the long-term and short-term relaxation effects [35], and in many studies, using one RC pair has shown accurate enough performance [28], [36]....
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TL;DR: In this paper, the effects of cold temperatures on the capacity/power fade of Li-ion battery technology are discussed, along with thermal strategies and the ideal approach to cold-temperature operation.
711 citations
TL;DR: In this paper, Li-ion battery thermal management systems (BTMSs) including the air, liquid, boiling, heat pipe and solid-liquid phase change based strategies are discussed.
675 citations
TL;DR: In this paper, a double-layer hierarchical control strategy was proposed to overcome the control challenge associated with coordination of multiple batteries within one stand-alone microgrid, where the unit-level primary control layer was established by an adaptive voltage-droop method aimed to regulate the common bus voltage and to sustain the states of charge (SOCs) of batteries close to each other during moderate replenishment.
Abstract: DC power systems are gaining an increasing interest in renewable energy applications because of the good matching with dc output type sources such as photovoltaic (PV) systems and secondary batteries. In this paper, several distributed generators (DGs) have been merged together with a pair of batteries and loads to form an autonomous dc microgrid (MG). To overcome the control challenge associated with coordination of multiple batteries within one stand-alone MG, a double-layer hierarchical control strategy was proposed. 1) The unit-level primary control layer was established by an adaptive voltage-droop method aimed to regulate the common bus voltage and to sustain the states of charge (SOCs) of batteries close to each other during moderate replenishment. The control of every unit was expanded with unit-specific algorithm, i.e., finish-of-charging for batteries and maximum power-point tracking (MPPT) for renewable energy sources, with which a smooth online overlap was designed and 2) the supervisory control layer was designed to use the low-bandwidth communication interface between the central controller and sources in order to collect data needed for adaptive calculation of virtual resistances (VRs) as well as transit criteria for changing unit-level operating modes. A small-signal stability for the whole range of VRs. The performance of developed control was assessed through experimental results.
631 citations
Additional excerpts
...age source followed with one R and two RC elements has been developed for lithium-ion battery in [29] and is showed in Fig....
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References
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30 Aug 2001
TL;DR: In this article, the authors present the principles of operation and reactions factors affecting battery performance standardization of battery design selection and application of batteries, as well as a discussion of the differences between primary and secondary batteries.
Abstract: Part 1 Principles of operation: basic concepts electrochemical principles and reactions factors affecting battery performance standardization of batteries battery design selection and application of batteries. Part 2 Primary batteries: zinc-carbon (Leclanche) cells magnesium and aluminium cells alkaline-manganese dioxide cells mercuric oxide cells silver oxide cells zinc/air cells lithium cells solid electrolyte batteries. Part 3 Reserve batteries: magnesium water-activated batteries spin-dependent reserve batteries liquid ammonia systems lithium anode reserve batteries thermal batteries. Part 4 Secondary batteries: lead acid batteries industrial nickel-cadmium batteries vented nickel-cadmium batteries sealed nickel-cadmium batteries nickel-zinc batteries iron electrode batteries silver-oxide batteries nickel-hydrogen batteries nickel-metal hydride batteries rechargeable alkaline-manganese dioxide batteries. Part 5 Advanced battery systems: ambient temperature lithium batteries zinc/bromine batteries metal/air batteries lithium/iron sulphide batteries sodium beta batteries.
2,185 citations
TL;DR: In this article, the authors present a complete dynamic model of a lithium ion battery that is suitable for virtual prototyping of portable battery-powered systems, based on publicly available data such as the manufacturers' data sheets.
Abstract: Presents here a complete dynamic model of a lithium ion battery that is suitable for virtual-prototyping of portable battery-powered systems. The model accounts for nonlinear equilibrium potentials, rate- and temperature-dependencies, thermal effects and response to transient power demand. The model is based on publicly available data such as the manufacturers' data sheets. The Sony US18650 is used as an example. The model output agrees both with manufacturer's data and with experimental results. The model can be easily modified to fit data from different batteries and can be extended for wide dynamic ranges of different temperatures and current rates.
784 citations
"Accurate electrical battery model c..." refers background in this paper
...4-V error voltage for constant charge and discharge currents; [20] models the nonlinear relation between the open-circuit voltage and SOC, but ignores the transient behavior; [21], [22] and [24] need additional mathematical equations to obtain the SOC and estimate TABLE I COMPARISON OF VARIOUS CIRCUIT MODELS...
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TL;DR: In this article, a mathematical model of a lead-acid battery is presented, which takes into account self-discharge, battery storage capacity, internal resistance, overvoltage, and environmental temperature.
Abstract: A mathematical model of a lead-acid battery is presented. This model takes into account self-discharge, battery storage capacity, internal resistance, overvoltage, and environmental temperature. Nonlinear components are used to represent the behavior of the different battery parameters thereby simplifying the model design. The model components are found by using manufacturers specifications and experimental tests. A comparison between the model and experimental results obtained from a battery evaluation test system was used for verification. This model can be used to accurately evaluate battery performance in electrical systems. >
637 citations
TL;DR: In this paper, the main results of studies that have been carried out, during a period of more than a decade, at University of Pisa in co-operation with other technical Italian institutions, about models of electrochemical batteries suitable for the use of the electrical engineer, in particular for the analysis of electrical systems with batteries.
Abstract: This paper documents the main results of studies that have been carried out, during a period of more than a decade, at University of Pisa in co-operation with other technical Italian institutions, about models of electrochemical batteries suitable for the use of the electrical engineer, in particular for the analysis of electrical systems with batteries. The problem of simulating electrochemical batteries by means of equivalent electric circuits is defined in a general way; then particular attention is then devoted to the problem of modeling of lead-acid batteries. For this kind of battery, a general model structure is defined from which specific models can be inferred, having different degrees of complexity and simulation quality. In particular, the implementation of the third-order model, that shows a good compromise between complexity and precision, is developed in detail. The behavior of the proposed models is compared with results obtained with extensive lab tests on different types of lead-acid batteries.
592 citations
"Accurate electrical battery model c..." refers background in this paper
...4-V error voltage for constant charge and discharge currents; [20] models the nonlinear relation between the open-circuit voltage and SOC, but ignores the transient behavior; [21], [22] and [24] need additional mathematical equations to obtain the SOC and estimate TABLE I COMPARISON OF VARIOUS CIRCUIT MODELS...
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TL;DR: Research in battery-aware optimization is now moving from stand-alone devices to networks of wireless devices, specifically, ad hoc and distributed sensor networks.
Abstract: Advances in battery technology have not kept pace with rapidly growing energy demands. Most laptops, handheld PCs, and cell phones use batteries that take anywhere from 1.5 to 4 hours to fully charge but can run on this charge for only a few hours. The battery has thus become a key control parameter in the energy management of portables. To meet the stringent power budget of these devices, researchers have explored various architectural, hardware, software, and system-level optimizations to minimize the energy consumed per useful computation. Research in battery-aware optimization is now moving from stand-alone devices to networks of wireless devices, specifically, ad hoc and distributed sensor networks. Computationally feasible mathematical models are now available that capture battery discharge characteristics in sufficient detail to let designers develop an optimization strategy that extracts maximum charge.
450 citations
"Accurate electrical battery model c..." refers background in this paper
...Digital Object Identifier 10.1109/TEC.2006.874229 because of the complicated physical and dynamic properties of batteries [1]....
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