UAS based Li-ion battery model parameters estimation

Ali, Daniyal; Mukhopadhyay, Shayok; Rehman, Habibur; Khurram, Adil

doi:10.1016/j.conengprac.2017.06.012

Cited by 33 publications

(76 citation statements)

References 25 publications

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“…Complex and accurate models exist for batteries, for which parameter identification requires a lot of experimental effort. So, the work in [23], [24] successfully identifies parameters of a reasonably accurate model with reduced experimental effort, and without extensive computational effort, via UAS. Similarly, there are several nonlinear models that have been formulated for supercapacitors, including fractional order models and associated parameter identification techniques, which were shown to be accurate.…”

Section: Introductionmentioning

confidence: 99%

Supercapacitor Characterization Using Universal Adaptive Stabilization and Optimization

Mukhopadhyay

Dhaouadi

Takrouri

et al. 2020

IEEE Open J. Ind. Electron. Soc.

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This paper presents a simplified supercapacitor model and a universal adaptive stabilization, optimization (UAS+O) based parameter identification technique. Analytic solutions for the description of supercapacitors current, voltage, subject to cyclic voltage and current sources of varying amplitudes and frequency, consistent with electric vehicle driving cycles, are developed. Supercapacitor I-V relationships show hysteresis, indicating simultaneous energy storage and dissipation mechanisms. A reduced equivalent circuit model is proposed to accurately represent hysteresis I-V characteristics. The proposed UAS+O based technique for estimating model parameters, is supported by mathematical proofs, simulation, and experimental results.

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Section: Introductionmentioning

confidence: 99%

Supercapacitor Characterization Using Universal Adaptive Stabilization and Optimization

Mukhopadhyay

Dhaouadi

Takrouri

et al. 2020

IEEE Open J. Ind. Electron. Soc.

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show abstract

“…Further, if the temperature of a Li-ion battery reaches around 60 • C, then there is a risk of thermal runaway, which may lead to an explosion and fire [8]. Motivated by the need to combat such issues, researchers have developed models and techniques for predicting battery behavior [9][10][11][12][13][14][15][16][17]. Methods to determine parameters of a thermal model of a Li-ion battery were reviewed in [9].…”

Section: Introductionmentioning

confidence: 99%

“…Battery models that focus on thermal behavior were described in [12][13][14]. Literature also exists on special techniques for Li-ion battery model parameter estimation, which can reduce the number of experiments required for estimating battery parameters [15]. Observers have also been used to estimate internal states of batteries [16].…”

Section: Introductionmentioning

confidence: 99%

Using Small Capacity Fuel Cells Onboard Drones for Battery Cooling: An Experimental Study

et al. 2018

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Recently, quadrotor-based drones have attracted a lot of attention because of their versatility, which makes them an ideal medium for a variety of applications, e.g., personal photography, surveillance, and the delivery of lightweight packages. The flight duration of a drone is limited by its battery capacity. Increasing the payload capacity of a drone requires more current to be supplied by the battery onboard a drone. Elevated currents through a Li-ion battery can increase the battery temperature, thus posing a significant risk of fire or explosion. Li-ion batteries are suited for drone applications, due to their high energy density. There have been attempts to use hydrogen fuel cells onboard drones. Fuel cell stacks and fuel tank assemblies can have a high energy to weight ratio. So, they may be able to power long duration drone flights, but such fuel cell stacks and associated systems, are usually extremely expensive. Hence, this work proposes the novel use of a less expensive, low capacity, metal hydride fuel stick-powered fuel cell stack as an auxiliary power supply onboard a drone. A primary advantage of this is that the fuel sticks can be used to cool the batteries, and a side effect is that this slightly reduces the burden on the onboard Li-ion battery and provides a small increment in flight time. This work presents the results of an experimental study which shows the primary effect (i.e., decrease in battery temperature) and the secondary side effect (i.e., a small increment in flight time) obtained by using a fuel cell stack. In this work, a metal hydride fuel stick powered hydrogen fuel cell is used along with a Li-ion battery onboard a drone.

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“…The electric elements in the circuit can be denoted by a combination of linear and exponential models to attune for the dynamic processes in the battery. The resultant circuits provide computationally efficient models, without requiring time-consuming laboratory measurements for the estimation of battery parameters [9].…”

mentioning

confidence: 99%

“…Ali et al developed a methodology for the non-linear estimation of Li-ion battery parameters in an equivalent circuit model [9]. The estimated parameters reflect the dynamic processes by characterizing the elements in the equivalent circuit model as a function of the SOC.…”

mentioning

confidence: 99%

Non-Ideal Linear Operation Model for Li-Ion Batteries

Gonzalez-Castellanos

Pozo

Bischi

2020

IEEE Trans. Power Syst.

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Currently, the characterization of electric energy storage units used for power system operation and planning models relies on two major assumptions: charge and discharge efficiencies, and power limits are constant and independent of the electric energy storage state of charge. This approach can misestimate the available storage flexibility.This work proposes a detailed model for the characterization of steady-state operation of Li-ion batteries in optimization problems. The model characterizes the battery performance, including non-linear charge and discharge power limits and efficiencies, as a function of the state of charge and requested power. We then derive a linear reformulation of the model without introducing binary variables, which achieves high computational efficiency, while providing high approximation accuracy. The proposed model characterizes more accurately the performance and technical operational limits associated with Li-ion batteries than those present in classical ideal models.The developed battery model has been compared with three modelling approaches: the complete non-convex formulation; an ideal model typically used in the power system community; and a mixed integer linear reformulation approach. The models have been tested on a network-constrained economic dispatch for a 24bus system. Based on the simulations, we observed approximately 12% of energy mismatches between schedules that use an ideal model and those that use the model proposed in this study.

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UAS based Li-ion battery model parameters estimation

Cited by 33 publications

References 25 publications

Supercapacitor Characterization Using Universal Adaptive Stabilization and Optimization

Supercapacitor Characterization Using Universal Adaptive Stabilization and Optimization

Using Small Capacity Fuel Cells Onboard Drones for Battery Cooling: An Experimental Study

Non-Ideal Linear Operation Model for Li-Ion Batteries

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