Abstract
This paper mainly investigates the sensitive characteristics of lithium-ion batteries so as to provide scientific basises for simplifying the design of the state estimator that adapt to various environments. Three lithium-ion batteries are chosen as the experimental samples. The samples were tested at various temperatures (−20 ∘ C, −10 ∘ C, 0 ∘ C , 10 ∘ C , 25 ∘ C) and various current rates (0.5C, 1C, 1.5C) using a battery test bench. A physical equivalent circuit model is developed to capture the dynamic characteristics of the batteries. The experimental results show that all battery parameters are time-varying and have different sensitivity to temperature, current rate and state of charge (SOC). The sensitivity of battery to temperature, current rate and SOC increases the difficulty in battery modeling because of the change of parameters. The further simulation experiments show that the model output has a higher sensitivity to the change of ohmic resistance than that of other parameters. Based on the experimental and simulation results obtained here, it is expected that the adaptive parameter state estimator design could be simplified in the near future.
Highlights
Nowadays, fossil fuel resources are running out and environmental pollution is serious [1,2].In response to the energy crisis and the increasing pollution problems, interests in electric vehicles (EVs) have grown in recent years [3]
Owing to the high-energy density, high-power density, low self-discharge rate and other merits compared with other batteries, lithium-ion batteries have been the first-choice candidate as a power source for EVs [7,8,9,10]
Accurate estimates for state of charge (SOC), state of health (SOH) and other states are needed over the lifetime of the battery pack in order to lengthen the useful lifetime of batteries
Summary
Fossil fuel resources are running out and environmental pollution is serious [1,2]. Precise modeling and accurate state estimation at various actual conditions for such systems have always been big challenges for researchers [19]. To be able to accurately estimate the battery states, it is necessary to maintain the nonlinear characterization of the system dynamic [4] and design a new nonlinear adaptive observer instead of EKF for the time-varying parameter system. It is a big challenge to design an observer for the battery system because all of the parameters are time-varying To this end, the sensitive properties of lithium-ion batteries are investigated here by the offline data. The main objective of these sensitive characteristics analysis is to find the dominant parameters that influence the battery model accuracy so as to simplify the adaptive parameter state estimator design.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
