Effect of U-Flex-to-Install and Dynamic U-Flexing On Li-Ion Battery SOH Degradation Subjected to Varying Fold Orientations, Folding Speeds, Depths of Charge, C-Rates and Temperatures

2021 ◽  
Author(s):  
Pradeep Lall ◽  
Ved Soni ◽  
Scott Miller
Keyword(s):  
Mechanical Stress ◽  
Standardized Test ◽  
Mechanical Test ◽  
Power Source ◽  
Body Motion ◽  
Power Sources ◽  
Biomedical Equipment ◽  
Capacity Degradation ◽  
Battery Capacity ◽  
Li Ion

Abstract The demand for wearable consumer electronics, fitness accessories and biomedical equipment has led to the growth research and development of thin flexible batteries. Wearable equipment and other asset monitoring applications require conformal installation of power sources on non-planar surfaces. For power sources in wearable electronics, durability to sustain repetitive mechanical stresses induced by human body motion is paramount along with the usual desirable power source characteristics. Previous research documenting the reliability of statically and dynamically folded power sources is scarce and does not follow standardized test protocols. Particularly, the use of manual stressing for mechanical folding of the power sources instead of a mechanical test setup is a key shortcoming in existing literature. Data is lacking on battery life cycling and in-situ mechanical stress-testing of the power sources including their impact of performance and reliability. Present study aims to overcome these deficiencies by testing a commercial Li-ion power source under static as well as dynamic folding. Furthermore, the fold-orientation and its fold-speed are varied to evaluate the effect of different mechanical stress topologies on the power source. Finally, a regression model was developed to capture the effect of these use parameters on battery capacity degradation.

Effect of Flex-to-Install and Dynamic Folding on Li-Ion Battery Performance Degradation Subjected to Varying Orientations, Folding Speeds, Depths of Charge and C-Rates

2020 ◽  
Author(s):  
Pradeep Lall ◽  
Ved Soni ◽  
Scott Miller
Keyword(s):  
Research And Development ◽  
Real Life ◽  
Rate Capability ◽  
Power Source ◽  
Power Sources ◽  
Biomedical Equipment ◽  
Capacity Degradation ◽  
Battery Capacity ◽  
Li Ion ◽  
Dynamic Folding

Abstract The growing need for wearable devices, fitness accessories and biomedical equipment has led to the upsurge in research and development of thin flexible battery research and development. Wearable equipment and other asset monitoring applications require versatile installation of power sources on non-planar surfaces. For power sources in wearable electronics, perseverance towards repetitive mechanical stresses induced by human body motion is necessary along with the usual desirable characteristics such as high capacity, high C-rate capability and good life cycle stability. Prior studies which document the reliability of power sources subject to static and dynamic folding are scarce and at times fail to follow definitive test protocols which limit their application to real-life battery use scenarios. Particularly, the use of manual mechanical stressing of the power sources instead of a mechanical test setup is a key shortcoming in existing literature. Data is lacking on battery life cycling and in-situ mechanical stressing of the power sources including their impact of performance and reliability. Present study aims to overcome these deficiencies by testing a commercial Li-ion power source under static as well as dynamic folding. Furthermore, the fold-orientation and its fold-speed are varied to evaluate the effect of different mechanical stress topologies on the power source. Finally, a regression model was developed to capture the effect of these use parameters on battery capacity degradation.

Capacity Loss Estimation For Li-Ion Batteries Based On A Semi-Empirical Model

2021 ◽  
Author(s):  
Mohammed Rabah ◽  
Eero Immonen ◽  
Sajad Shahsavari ◽  
Mohammad-Hashem Haghbayan ◽  
Kirill Murashko ◽  
...  
Keyword(s):  
Lithium Ion Batteries ◽  
Empirical Model ◽  
Lithium Ion ◽  
Average Error ◽  
Li Ion Batteries ◽  
Capacity Loss ◽  
Capacity Degradation ◽  
Battery Capacity ◽  
Li Ion ◽  
Semi Empirical

Understanding battery capacity degradation is instrumental for designing modern electric vehicles. In this paper, a Semi-Empirical Model for predicting the Capacity Loss of Lithium-ion batteries during Cycling and Calendar Aging is developed. In order to redict the Capacity Loss with a high accuracy, battery operation data from different test conditions and different Lithium-ion batteries chemistries were obtained from literature for parameter optimization (fitting). The obtained models were then compared to experimental data for validation. Our results show that the average error between the estimated Capacity Loss and measured Capacity Loss is less than 1.5% during Cycling Aging, and less than 2% during Calendar Aging. An electric mining dumper, with simulated duty cycle data, is considered as an application example.

Life-Assessment for Thin Flexible Batteries Under U-Flex-to-Install and Dynamic Folding

2021 ◽  
Author(s):  
Pradeep Lall ◽  
Ved Soni ◽  
Scott Miller
Keyword(s):  
Research And Development ◽  
Real Life ◽  
High Capacity ◽  
Rate Capability ◽  
Life Assessment ◽  
Wearable Electronics ◽  
Power Sources ◽  
Biomedical Equipment ◽  
Capacity Degradation ◽  
Dynamic Folding

Abstract The growing need for wearable devices, fitness accessories and biomedical equipment has led to the upsurge in research and development of thin flexible battery research and development. The current state of art wearable electronics products being developed in several fields require installation of power sources in different configurations and at times require the battery to undergo mechanical folding during product operation. This requires the product batteries to robustly withstand the imposed mechanical stresses during use along with the other desirable characteristics attributed to the power source such as high C-rate capability, high capacity and low capacity degradation rate. Works that explore the effects of static and dynamic folding on li-ion power sources is limited and oftentimes doesn’t adhere to definite test protocols resulting in non-standardized experimental data that can’t be applied to real-life product scenarios. Specifically, the effect of fold diameter on the battery state of health degradation when subjected to both static and dynamic folding is not yet completely explored. Present study aims to address this gap in the literature by investigating the effect of varying the fold diameter is both static (U-flex-to-install) and dynamic (dynamic U-fold) tests. Four different values of fold diameters have been chosen for experimentation and to study its effect during the aforementioned tests. Multiple samples have been tested for a given test condition so as to generate high fidelity data. Ultimately, a regression model developed previously has been augmented with the results generated in the current study.

Experimental verification of lithium-ion battery prognostics based on an interacting multiple model particle filter

2020 ◽  
pp. 014233122096157
Author(s):  
Shuai Wang ◽  
Wei Han ◽  
Lifei Chen ◽  
Xiaochen Zhang ◽  
Michael Pecht
Keyword(s):  
Particle Filter ◽  
Lithium Ion ◽  
Remaining Useful Life ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Li Ion Batteries ◽  
Model Particle ◽  
Capacity Degradation ◽  
Battery Capacity ◽  
Li Ion

A new data-driven prognostic method based on an interacting multiple model particle filter (IMMPF) is proposed for use in the determination of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries and the probability distribution function (PDF) of the uncertainty associated with the RUL. An IMMPF is applied to different state equations. The battery capacity degradation model is very important in the prediction of the RUL of Li-ion batteries. The IMMPF method is applied to the estimation of the RUL of Li-ion batteries using the three improved models. Three case studies are provided to validate the proposed method. The experimental results show that the one-dimensional state equation particle filter (PF) is more suitable for estimating the trend of battery capacity in the long term. The proposed method involving interacting multiple models demonstrated a stable and high prediction accuracy, as well as the capability to narrow the uncertainty in the PDF of the RUL prediction for Li-ion batteries.

Maintaining a Constant Charging Duration Independent of Battery Capacity for Battery Pack by Designing a Fast DC Charger

2019 ◽  
Vol 8 (3) ◽  
pp. 102-116
Author(s):  
Bassam Atieh ◽  
Mohammad Fouad Al-sammak
Keyword(s):  
Lower Cost ◽  
Lithium Ion ◽  
Power Source ◽  
Battery Pack ◽  
Simulation Environment ◽  
Electronic Components ◽  
Battery Capacity ◽  
Li Ion ◽  
Novel Strategy ◽  
Usage Flexibility

This article proposes a novel strategy for developing a new structure for a lithium-ion battery pack fast charger which aims to achieve fast DC charging, based on the topology of a boost converter. The proposed charger has been designed considering using fewer electronic components at lower cost. Varying initial charging percentage of the Li-ion cells has not been addressed in this article, an equal initial charging percentage of each Li-ion cell is assumed. Performance of the proposed structure of the charger has been tested using a simulation environment. This strategy has shown that this structure ensures scalability of this charger, while using the utility grid (220V, 50Hz) as a main power source for this charger has ensured practical usage flexibility. The results of this research are presented and discussed. These results have shown the outstanding performance and response of this charger.

Effect of Charge-Discharge Depth and Environment Use Conditions on Flexible Power Sources

2019 ◽  
Author(s):  
Pradeep Lall ◽  
Ved Soni ◽  
Amrit Abrol ◽  
Ben Leever ◽  
Scott Miller
Keyword(s):  
High Temperatures ◽  
High Capacity ◽  
Form Factors ◽  
Lithium Ion ◽  
Consumer Electronics ◽  
Cycle Number ◽  
Power Sources ◽  
Capacity Degradation ◽  
Battery Capacity ◽  
Charge Discharge

Abstract Recent surge in demand for wearable technology products such as activity tracking smartwatches, and for medical devices has necessitated development of flexible secondary lithium ion batteries which also possess high capacity, robustness and thin form factors. Oftentimes, these power sources are only charged up to a partial state of charge (SoC) before use (shallow charge). Their usage continues until the SoC reaches almost zero, after which they are recharged again. Nowadays, the ‘fast-charge ‘feature used to charge the battery at higher C-rates, is a necessity in consumer electronics rather than an amenity. Also, in everyday use, these batteries are exposed to higher-than-ambient temperatures due to perpetual human body contact and also to the high temperatures resulting from poor thermal management in compact devices. This study investigates the compounded influence of partial charge, high temperatures and high C-rates on the capacity degradation of a flexible Li-ion power source subjected to accelerated life testing. The battery current and terminal voltage were logged for multiple charge-discharge cycles and were used to compute the battery capacity and energy efficiency. Finally, a regression model based on several parameters was developed to estimate the battery capacity as a function of the cycle number.

scholarly journals Induced Effects of Environmentally Friendly Generations in Korea

2021 ◽  
Vol 13 (8) ◽  
pp. 4404
Author(s):  
Ji Whan Kim ◽  
Yoon Kyung Kim
Keyword(s):  
Wind Power ◽  
Environmentally Friendly ◽  
Energy Transition ◽  
Power Source ◽  
Economic Effects ◽  
Offshore Wind ◽  
Major Power ◽  
Power Sources ◽  
Onshore Wind ◽  
Production Effect

This study estimated the induced effects of LNG, mega PV (photovoltaic), small PV, onshore wind and offshore wind power, which will be used as major power sources under the Korea’s energy transition policy. The 2015 Input–Output Statistics of Bank of Korea were used to reflect Korea’s economic structure. The MCI (manufacture, construction and installation) and O&M (operation and maintenance) of each power source would have different effects, so in the analysis the MCI and O&M of each power source were distinguished. According to estimation results, the induced-effect coefficients of the MCI are greater than those of the O&M in every power source. The induced production effect coefficient of the MCI is decreased in the order of mega PV > small PV > LNG power > offshore wind > onshore wind. The induced production effect coefficient of the O&M is decreased in the order of mega PV > small PV > onshore wind > offshore wind > LNG thermal. The induced employment coefficient of the MCI is decreased in the order of LNG thermal > mega PV > small PV > onshore wind > offshore wind. PV power and wind power have bigger induced effects and bring economic effects in Korean economy. The carbon neutrality and energy transition policies implemented by Korea have a certain level of induced effects and offset the burden of transition costs even if existing power sources are replaced with environmentally friendly power sources.

scholarly journals Adaptive State-of-Charge Estimation for Lithium-Ion Batteries by Considering Capacity Degradation

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 122
Author(s):  
Peipei Xu ◽  
Junqiu Li ◽  
Chao Sun ◽  
Guodong Yang ◽  
Fengchun Sun
Keyword(s):  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Maximum Error ◽  
State Of Charge ◽  
Recursive Least Squares ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Soc Estimation ◽  
Capacity Degradation ◽  
Battery Capacity

The accurate estimation of a lithium-ion battery’s state of charge (SOC) plays an important role in the operational safety and driving mileage improvement of electrical vehicles (EVs). The Adaptive Extended Kalman filter (AEKF) estimator is commonly used to estimate SOC; however, this method relies on the precise estimation of the battery’s model parameters and capacity. Furthermore, the actual capacity and battery parameters change in real time with the aging of the batteries. Therefore, to eliminate the influence of above-mentioned factors on SOC estimation, the main contributions of this paper are as follows: (1) the equivalent circuit model (ECM) is presented, and the parameter identification of ECM is performed by using the forgetting-factor recursive-least-squares (FFRLS) method; (2) the sensitivity of battery SOC estimation to capacity degradation is analyzed to prove the importance of considering capacity degradation in SOC estimation; and (3) the capacity degradation model is proposed to perform the battery capacity prediction online. Furthermore, an online adaptive SOC estimator based on capacity degradation is proposed to improve the robustness of the AEKF algorithm. Experimental results show that the maximum error of SOC estimation is less than 1.3%.

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