The Experts below are selected from a list of 16083 Experts worldwide ranked by ideXlab platform
Dirk Uwe Sauer - One of the best experts on this subject based on the ideXlab platform.
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on line adaptive battery Impedance Parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2 Parameter and state estimation
Journal of Power Sources, 2014Co-Authors: Christian Fleischer, Wladislaw Waag, Hansmartin Heyn, Dirk Uwe SauerAbstract:Abstract Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online Parameter identification technique based on a weighted recursive least quadratic squares Parameter estimator to determine the Parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery Parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of Parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.
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on line adaptive battery Impedance Parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 1 requirements critical review of methods and modeling
Journal of Power Sources, 2014Co-Authors: Christian Fleischer, Wladislaw Waag, Hansmartin Heyn, Dirk Uwe SauerAbstract:Abstract Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored, these include: battery state of charge (SoC), battery state of health (capcity fade determination, SoH), and state of function (power fade determination, SoF). In a series of two papers, we propose a system of algorithms based on a weighted recursive least quadratic squares Parameter estimator, that is able to determine the battery Impedance and diffusion Parameters for accurate state estimation. The functionality was proven on different battery chemistries with different aging conditions. The first paper investigates the general requirements on BMS for HEV/EV applications. In parallel, the commonly used methods for battery monitoring are reviewed to elaborate their strength and weaknesses in terms of the identified requirements for on-line applications. Special emphasis will be placed on real-time capability and memory optimized code for cost-sensitive industrial or automotive applications in which low-cost microcontrollers must be used. Therefore, a battery model is presented which includes the influence of the Butler–Volmer kinetics on the charge-transfer process. Lastly, the mass transport process inside the battery is modeled in a novel state-space representation.
Christian Fleischer - One of the best experts on this subject based on the ideXlab platform.
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on line adaptive battery Impedance Parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2 Parameter and state estimation
Journal of Power Sources, 2014Co-Authors: Christian Fleischer, Wladislaw Waag, Hansmartin Heyn, Dirk Uwe SauerAbstract:Abstract Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online Parameter identification technique based on a weighted recursive least quadratic squares Parameter estimator to determine the Parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery Parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of Parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.
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on line adaptive battery Impedance Parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 1 requirements critical review of methods and modeling
Journal of Power Sources, 2014Co-Authors: Christian Fleischer, Wladislaw Waag, Hansmartin Heyn, Dirk Uwe SauerAbstract:Abstract Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored, these include: battery state of charge (SoC), battery state of health (capcity fade determination, SoH), and state of function (power fade determination, SoF). In a series of two papers, we propose a system of algorithms based on a weighted recursive least quadratic squares Parameter estimator, that is able to determine the battery Impedance and diffusion Parameters for accurate state estimation. The functionality was proven on different battery chemistries with different aging conditions. The first paper investigates the general requirements on BMS for HEV/EV applications. In parallel, the commonly used methods for battery monitoring are reviewed to elaborate their strength and weaknesses in terms of the identified requirements for on-line applications. Special emphasis will be placed on real-time capability and memory optimized code for cost-sensitive industrial or automotive applications in which low-cost microcontrollers must be used. Therefore, a battery model is presented which includes the influence of the Butler–Volmer kinetics on the charge-transfer process. Lastly, the mass transport process inside the battery is modeled in a novel state-space representation.
Hansmartin Heyn - One of the best experts on this subject based on the ideXlab platform.
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on line adaptive battery Impedance Parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2 Parameter and state estimation
Journal of Power Sources, 2014Co-Authors: Christian Fleischer, Wladislaw Waag, Hansmartin Heyn, Dirk Uwe SauerAbstract:Abstract Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online Parameter identification technique based on a weighted recursive least quadratic squares Parameter estimator to determine the Parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery Parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of Parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.
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on line adaptive battery Impedance Parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 1 requirements critical review of methods and modeling
Journal of Power Sources, 2014Co-Authors: Christian Fleischer, Wladislaw Waag, Hansmartin Heyn, Dirk Uwe SauerAbstract:Abstract Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored, these include: battery state of charge (SoC), battery state of health (capcity fade determination, SoH), and state of function (power fade determination, SoF). In a series of two papers, we propose a system of algorithms based on a weighted recursive least quadratic squares Parameter estimator, that is able to determine the battery Impedance and diffusion Parameters for accurate state estimation. The functionality was proven on different battery chemistries with different aging conditions. The first paper investigates the general requirements on BMS for HEV/EV applications. In parallel, the commonly used methods for battery monitoring are reviewed to elaborate their strength and weaknesses in terms of the identified requirements for on-line applications. Special emphasis will be placed on real-time capability and memory optimized code for cost-sensitive industrial or automotive applications in which low-cost microcontrollers must be used. Therefore, a battery model is presented which includes the influence of the Butler–Volmer kinetics on the charge-transfer process. Lastly, the mass transport process inside the battery is modeled in a novel state-space representation.
Wladislaw Waag - One of the best experts on this subject based on the ideXlab platform.
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on line adaptive battery Impedance Parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 2 Parameter and state estimation
Journal of Power Sources, 2014Co-Authors: Christian Fleischer, Wladislaw Waag, Hansmartin Heyn, Dirk Uwe SauerAbstract:Abstract Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored. These include: battery state of charge (SoC), battery state of health (capacity fade determination, SoH), and state of function (power fade determination, SoF). The second paper concludes the series by presenting a multi-stage online Parameter identification technique based on a weighted recursive least quadratic squares Parameter estimator to determine the Parameters of the proposed battery model from the first paper during operation. A novel mutation based algorithm is developed to determine the nonlinear current dependency of the charge-transfer resistance. The influence of diffusion is determined by an on-line identification technique and verified on several batteries at different operation conditions. This method guarantees a short response time and, together with its fully recursive structure, assures a long-term stable monitoring of the battery Parameters. The relative dynamic voltage prediction error of the algorithm is reduced to 2%. The changes of Parameters are used to determine the states of the battery. The algorithm is real-time capable and can be implemented on embedded systems.
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on line adaptive battery Impedance Parameter and state estimation considering physical principles in reduced order equivalent circuit battery models part 1 requirements critical review of methods and modeling
Journal of Power Sources, 2014Co-Authors: Christian Fleischer, Wladislaw Waag, Hansmartin Heyn, Dirk Uwe SauerAbstract:Abstract Lithium-ion battery systems employed in high power demanding systems such as electric vehicles require a sophisticated monitoring system to ensure safe and reliable operation. Three major states of the battery are of special interest and need to be constantly monitored, these include: battery state of charge (SoC), battery state of health (capcity fade determination, SoH), and state of function (power fade determination, SoF). In a series of two papers, we propose a system of algorithms based on a weighted recursive least quadratic squares Parameter estimator, that is able to determine the battery Impedance and diffusion Parameters for accurate state estimation. The functionality was proven on different battery chemistries with different aging conditions. The first paper investigates the general requirements on BMS for HEV/EV applications. In parallel, the commonly used methods for battery monitoring are reviewed to elaborate their strength and weaknesses in terms of the identified requirements for on-line applications. Special emphasis will be placed on real-time capability and memory optimized code for cost-sensitive industrial or automotive applications in which low-cost microcontrollers must be used. Therefore, a battery model is presented which includes the influence of the Butler–Volmer kinetics on the charge-transfer process. Lastly, the mass transport process inside the battery is modeled in a novel state-space representation.
Wang Zhi-guo - One of the best experts on this subject based on the ideXlab platform.
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Research on lead-acid battery Impedance Parameters identification system based on LabVIEW
Chinese Journal of Power Sources, 2009Co-Authors: Wang Zhi-guoAbstract:The Impedance Parameter identification system for lead-acid battery based on LabVIEW was studied in this paper.The general scheme and the specific design of software hardware were proposed based on the integrated analysis of lead-acid battery Impedance.And meanwhile,a method to realize the frequency conversion AC constant current source by visual instrument was presented,which has achieved the online and real time identification of lead-acid battery Impedance Parameters.Therefore,this method has a high practical value and is worth of popularizing.
