A common way to model lithium-ion batteries is to apply equivalent circuit (EC) models. In this work two different EC models are build up and parameterized for a commercial 6.5 Ah high-power lithium-ion cell. Measured impedance spectroscopy data depending on temperature and state of charge (SOC) are used for parameter estimation.
The first EC model consists of an ohmic resistor (R), an inductor (L) and three RC-elements (a parallel connection of a capacitor (C) and a resistor). The second EC model consists of one R, one L, two Zarc elements and a Warburg element. The estimated parameters were used to develop two empirical electrical cell models which are able to predict the voltage of the cells depending on current, temperature and SOC. Hereby the internal cell resistance Ri is based on the EC models and a Butler–Volmer adjustment. Both approaches were validated by current profiles, which cover typical automotive applications to prove the model performance at low temperatures and high dynamic operation. An accurate voltage prediction could be realized with both EC models. The second, more complex, model is able to predict cell voltage more precisely, but at the expense of up to four times higher computational effort.
Article Outline
1. Introduction 2. Theory
2.1. Equivalent circuit with RC-elements
2.2. Equivalent circuit with Zarc and Warburg element 2.2.1. The Zarc element 2.2.2. The Warburg element 3. Parameter estimation
3.1. Equivalent circuit with RC-elements
3.2. Equivalent circuit with Zarc and Warburg element 4. Modelling
4.1. Butler–Volmer adjustment
4.2. Equivalent circuit with RC-elements
4.3. Equivalent circuit with Zarc and Warburg element 5. Validation
5.1. Stepwise discharge 5.2. Test cycle 5.3. Drive cycle
6. Results and discussion References
Research highlights
A branched oligomer additive with an imide structure was synthesized by Michael addition method. The membrane forms a self-polymerized solid electrolyte interface (SEI) after the battery has been electrochemically charged.
The specific SEI can promote secondary self-polymerization on the
A self-polymerized SEI membrane prevents
surface of the cathode at typical onset temperatures.
internal short circuits and the development of dangerous conditions in lithium ion battery.
There is much confusion and uncertainty in the literature concerning the useable power capability of batteries and ultracapacitors (electrochemical capacitors) for various applications. Clarification of this confusion is one of the primary objectives of this paper. The three approaches most often applied to determine the power capability of devices are (1) matched impedance power, (2) the min/max method of the USABC, and (3) the pulse energy efficiency approach used at UC Davis. It has been found that widely different power capability for batteries and ultracapacitors can be inferred using these approaches even when the resistance and open-circuit voltage are accurately known. In general, the values obtained using the energy efficiency method for EF = 90–95% are much lower than the other two methods which yield values corresponding to efficiencies of 70–75%. For plug-in hybrid and battery electric vehicle applications, the maximum useable power density for a lithium-ion battery can be higher than that corresponding to 95% efficiency because the peak power of the driveline is used less frequently and consequently charge/discharge efficiently is less important. For these applications, the useable power density of the batteries can be closer to the useable power density of ultracapacitors. In all cases, it is essential that a careful and appropriate measurement is made of the resistance of the devices and the comparisons of the useable power capability be made in a way appropriate for the application for which the devices are to be used.
Article Outline
1. Introduction
2. Definition and calculation of power capability 3. Experimental determination of the power capability 3.1. Ultracapacitors 3.2. Lithium-ion batteries
4. Comparisons of the power capability of ultracapacitors and batteries for vehicle applications 5. Summary and conclusions
Appendix A. Analysis of the discharge of ultracapacitors A.1. Constant power discharges of ultracapacitors A.2. Pulse power discharge of ultracapacitors A.3. Batteries
References
Biology presents incomparable, but desirable, characteristics compared to engineered systems. Inspired by biological development, we have devised a multi-layered design architecture that attempts to capture the favourable characteristics of biological mechanisms for application to design problems. We have identified and implemented essential features of Genetic Regulatory Networks (GRNs) and cell signalling which lead to self-organization and cell differentiation. We have applied this to electronic circuit design.
Article Outline
1. Introduction and motivation 2. Biology concepts and inspiration 2.1. Biology process
2.2. Multi-layered view of biology development 2.3. Genetic Regulatory Networks and feedback loops 2.4. Protein synthesis 2.5. Cell signalling
2.6. Degeneracy characteristics 2.6.1. Degeneracy in genetic regulation 2.6.2. Degeneracy in gene regulatory site 2.6.3. Degeneracy in protein folding 2.6.4. Degeneracy and evolution 2.6.5. Degeneracy impact on robustness 3. Related work in computational development 4. Biology-inspired model 4.1. Model structure 4.1.1. Genome layer 4.1.2. Protein layer 4.1.3. Mapping layer
4.2. Model components 4.2.1. Cell
4.2.2. Gene structure 4.2.3. Protein 4.2.4. Cell membrane 4.2.5. Cell membrane 4.2.6. Signalling pathway 4.3. Development process 4.3.1. Gene regulation network 4.3.2. Protein diffusion 4.3.3. Cell division 4.3.4. Cell signalling 4.3.5. Mapping process 5. Analysis
5.1. Stabilization of gene regulations 5.2. Stabilization of protein level 5.3. Regulation of cell differentiation
5.4. Evolution of regulation of cell differentiation 5.5. Evolution of differential regular regulation patterns 5.6. Cell signalling
5.7. Signalling at the application level 5.8. Degeneracy in design 6. Summary Acknowledgements References
As an initial electric fault occurs, the fault current would result in a strong magnetic force and torque exerted on the power line conductors. The rotational magnetic torque, in turn, would make the power
lines with sags swing and may bring them to close proximity or in contact with one another, causing a subsequent fault. For the analysis of the magnetically induced subsequent fault (MISFault), software has been developed as the end product of a multi-year research project sponsored by Duke Energy
Company. The software is capable of predicting the smallest distance between the power line conductors during their swing procedure, from which one can predict the probability of the magnetically induced subsequent fault; and determine the allowed span length range from consideration of eliminating the subsequent fault, which is anticipated to be useful for a utility in long span design. The software has been tested and the accuracy of its computation results has been validated by verifying that the energy conservation law requirement is well satisfied. The MISFault software is being used by Duke Energy Company. It is user friendly and is expected to be useful to a utility for eliminating the magnetically induced subsequent fault.
Article Outline
1. Introduction
2. Numerical techniques 3. Description of the software 4. Main functions of the software 4.1. General settings 4.2. Initialization 4.3. Computation
4.4. Data display and text report 5. Conclusions Acknowledgements References Vitae
Context
Coproduction of new products has been deemed successful in organizational partnerships by adding to the quality and scope of the product. Techniques that involve users during the development of software tend to mimic this environment, but differ in the type of product and internal client roles. The question is thus, whether coproduction improves the outcomes of a software development project as it has in other disciplines.
Objective
This paper evaluates how the coproduction relationship between software developers and users improves the outcomes of a development project. Coproduction is believed to improve outcomes when available knowledge is accessible and applicable to the objective of the development project. Should the relationships hold, coproduction approaches to development can be approached with confidence and improvements made by attention to the development and deployment of expertise.
Method
A quantitative questionnaire related to the coproduction environment was developed for four variables to include coproduction, applying expertise, locating expertise, and project success. 128 users from development teams responded to the survey and represent a variety of industries, individual characteristics, and project sizes.
Results
Expertise is crucial to the success of a software development project and coproduction improves the ability to access and apply the needed expertise. In addition, coproduction directly improves outcomes.
Conclusion
Coproduction can be an effective approach to the development of systems in terms of meeting project goals. Additionally, the assembly of expertise on the team is an important contributor to successful outcomes that may be enhanced through effective selection of team members. The ability to locate the
available expertise is crucial, indicating the value of team building functions to promote awareness of expertise location.
Article Outline
1. Introduction
2. Background and proposed research model 3. Research hypotheses 4. Research method 4.1. Sample 4.2. Constructs
4.3. Measurement model 5. Data analysis and results 6. Implications 7. Threats to validity Acknowledgements References
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