Transport Systems
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Browsing Transport Systems by Author "Auger, Daniel"
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Item Open Access Data for "Electric Vehicle Battery Parameter Identification and SOC Observability Analysis: NiMH and Li-S Case Studies"(Cranfield University, 2017-11-21 11:49) Fotouhi, Abbas; Auger, Daniel; Propp, Karsten; Longo, StefanoIn this study, battery model identification is performed to be applied in electric vehicle battery management systems. Two case studies are investigated: nickel-metal hydride (NiMH), which is a mature battery technology, and lithium-sulfur (Li-S), a promising next-generation technology. Equivalent circuit battery model parameterization is performed in both cases using the Prediction-Error Minimization (PEM) algorithm applied to experimental data. Performance of a Li-S cell is also tested based on urban dynamometer driving schedule (UDDS) and the proposed parameter identification framework is applied in this case as well. The identification results are then validated against the exact values of the battery parameters. The use of identified parameters for battery state-of-charge (SOC) estimation is also discussed. It is shown that the set of parameters needed can change with a different battery chemistry. In the case of NiMH, the battery open circuit voltage (OCV) is adequate for SOC estimation whereas Li-S battery SOC estimation is more challenging due to its unique features such as flat OCV-SOC curve. An observability analysis shows that Li-S battery SOC is not fully observable and the existing methods in the literature might not be applicable for a Li-S cell. Finally, the effect of temperature on the identification results and the observability are discussed by repeating the UDDS test at 5, 10, 20, 30, 40 and 50 degree Celsius. File created in MATLAB 2015a.Item Open Access Data for "Lithium-Sulfur Battery State-of-Charge Observability Analysis and Estimation"(Cranfield University, 2017-11-21 11:49) Fotouhi, Abbas; Auger, Daniel; Propp, Karsten; Longo, Stefano3.4 Ah Li-S cell pulse discharge test data at 30 degree. File created in MATLAB 2015a.Item Open Access Data for the paper "Analysis of Autopilot Disengagements Occurring during Autonomous Vehicle Testing"(Cranfield University, 2017-12-11 08:19) Lyu, Chen; Cao, Dongpu; Zhao, Yifan; Auger, Daniel; Sullman, Mark; Wang, HuajiData used in the paper "Analysis of Autopilot Disengagements Occurring during Autonomous Vehicle Testing".Item Embargo Data relating to "Li-S cell partial charge-discharge"(Cranfield University, 2024-11-07) Shateri, Neda; Auger, Daniel; Fotouhi, AbbasItem Open Access Dataset "A Novel Hybrid Electrochemical Equivalent Circuit Model for Online Battery Management Systems"(Cranfield University, 2024-08-02) Cai, Chengxi; Auger, DanielA Novel Hybrid Electrochemical Equivalent Circuit Model for Online Battery Management SystemsItem Open Access How accurate is state of charge as a predictor of remaining useful work? (ICLSB 2019)(Cranfield University, 2021-05-13 09:21) Auger, Daniel; Munisamy, Srinivasan; Fotouhi, AbbasPresentation given at ICLSB 2019. Abstract follows: It is well known that lithium sulfur cells have a distinctive open-circuit voltage profile: at high states of charge there is a €˜high plateau€™, starting at around 2.35 V, and at low states of charge there is a flatter €˜low plateau€™ at near constant voltage. This presentation will discuss the implications this profile might have for the prediction of the work that cell is capable of doing before it is fully discharged, which is vital for real-world applications. This presentation will introduce a family of techniques that has been developed for the creation of low-complexity dynamic models [1,2] and their application in state estimation algorithms embedded within real-life battery management systems using extended Kalman filters, unscented Kalman filters and particle filters [3,4] or adaptive neuro-fuzzy inference systems (ANFIS) [5]. So far, algorithms for management of lithium-sulfur have all been based on state of charge, rather than €˜remaining energy€™. In a practical application, the real information the end user needs is an answer to the question €˜how much work can I still do?€™ The work done by a cell is the product of the terminal voltage and the current delivered to the load, and a Coulomb-based metric, dependent on current alone, is only a proxy for this. In this presentation, we explore the question €˜how accurate is state of charge as a predictor of remaining useful work?€™ In this presentation, the title question is addressed, both using theoretical and simulation studies comparing a lithium-ion cell [6] from the literature with a model of development-grade industrial lithium sulfur cell [1] and through the analysis of experimental data collected from the same lithium-sulfur cell. In the theoretical studies, it is observed that with low currents, state of charge is a good predictor of remaining useful work in both the lithium-ion cell and the lithium-sulfur one, but that where the remaining useful work predictions for the lithium-ion cell are least accurate at the mid-discharge point, the remaining useful work predictions for the lithium-sulfur cell were least accurate near to the transition between the high and low plateau. The results of the theoretical analysis were supported by an analysis of the experimental data. From these results, no significant motivation was been identified for refactoring estimation algorithms in terms of state of energy. At the time this abstract is prepared, work to consider the accuracy of prediction of remaining useful work at higher loads is underway, and the results of this will also be presented at the conference. [1] Propp K, Marinescu M, Auger DJ, O'Neill L, Fotouhi A, Somasundaram K, Offer GJ, Minton G, Longo S, Wild M & Knap V (2016) Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries, Journal of Power Sources, 328 (October) 289-299. Dataset/s: 10.17862/cranfield.rd.c.3292031 [2] Fotouhi A, Auger DJ, Propp K, Longo S, Purkayastha R, O'Neill L & Walus S (2017) Lithium-Sulfur cell equivalent circuit network model parameterization and sensitivity analysis, IEEE Transactions on Vehicular Technology, 66 (9) 7711-7721. [3] Propp K, Auger DJ, Fotouhi A, Longo S & Knap V (2017) Kalman-variant estimators for state of charge in lithium-sulfur batteries, Journal of Power Sources, 343 (March) 254-267. Dataset/s: 10.17862/cranfield.rd.3834057 [4] Knap V, Auger DJ, Propp K, Fotouhi A & Stroe D-I (2018) Concurrent real-time estimation of state of health and maximum available power in lithium-sulfur batteries, Energies, 11 (2133) 1-23. [5] Fotouhi A, Auger D, Propp K & Longo S (2018) Lithium-sulfur battery state-of-charge observability analysis and estimation, IEEE Transactions on Power Electronics, 33 (7) 5847-5859. [6] Antaloae C, Marco J & Assadian F (2012) A novel method for the parameterization of a Li-ion cell model for EV/HEV control applications. IEEE Transactions on Vehicular Technology, 61(9), 3881€“3892. https://doi.org/10.1109/TVT.2012.2212474Item Open Access Kalman-variant estimators for state of charge in lithium-sulfur batteries(Cranfield University, 2022-05-01 01:10) Propp, Karsten; Auger, Daniel; Fotouhi, Abbas; Longo, Stefano; Knap, VaclavThis fileset is a set of MATLAB/Simulink R2016a models implementing state-of-charge estimators for lithium-sulfur batteries as described in the associated publications. The associated experimental data is also included. Instructions are included in a 'readme.txt' file in the root directory.Item Open Access MATLAB and Simulink Models for 'Improved State of Charge Estimation for Lithium-Sulfur Batteries'(Cranfield University, 2022-05-01 01:10) Auger, Daniel; Propp, Karsten; Fotouhi, Abbas; Marinescu, Monica; Knap, Vaclav; Longo, StefanoThis fileset consists of Simulink models of a state estimator for lithium-sulfur batteries, as described in a research paper that has been submitted for publication.Item Open Access Model validation data for 'Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries'(Cranfield University, 2022-05-01 01:10) Auger, Daniel; Fotouhi, Abbas; Longo, StefanoThis fileset contains the experimental data used for model validation in the paper 'Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries' accepted by the Journal of Power Sources on July 23, 2016. The data files can be opened with MATLAB R2016a.Item Open Access Parameter identification data from 'Multi-temperature state-dependent equivalent circuit discharge model'(Cranfield University, 2022-06-01 01:10) Auger, Daniel; Fotouhi, Abbas; Longo, StefanoThis fileset contains the experimental data used for parameter identification in the paper 'Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries' accepted by the Journal of Power Sources on July 23, 2016. The data files can be opened with MATLAB R2016a.Item Open Access Results of Centreline Extraction Based on Maximal Disks(Cranfield University, 2023-06-07 11:28) Yin, Chenhui; Cecotti, Marco; Auger, Daniel; Fotouhi, AbbasResults of centreline extraction based on maximal disks in a chosen lanelet2 map.Item Open Access Self-Discharge Resistance Values at Different Initial Charge and Temperature Levels(Cranfield University, 2017-11-22 08:45) Yousif, S E; Auger, Daniel; Fotouhi, Abbas; Propp, KarstenTable II: Self-discharge resistance values at different initial charge and temperature levels from 'Self-Discharge Effects in Lithium-Sulfur Equivalent Circuit Networks for State Estimation'. Opens with Microsoft Excel.Item Open Access Simulink models from 'Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries(Cranfield University, 2016-08-10 11:24) Auger, Daniel; Fotouhi, Abbas; Longo, StefanoThis fileset contains a Simulink representation of the models developed in the paper 'Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries' accepted by the Journal of Power Sources on July 23, 2016. The data files can be opened with Simulink R2016a.