Development of a converterless energy management system for reusing automotive lithium-ion battery applied in smart-grid balancing

Chiang, Yu Hsien; Sean, Wu-Yang; Wu, Chien-Hsun; Huang, Chung-Neng

doi:10.1016/j.jclepro.2017.04.028

Cited by 36 publications

(11 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Under this algorithm, the total spinning reserve of generator sets and energy storage device is close to and slightly higher than the total spinning reserve requirement of the system, and the energy storage device provides 50.40% alternative reserve at the peak of non‐load. However, the total spinning reserve demand of the power units and energy storage device of S1 and S2 algorithms are always lower than the total spinning reserve demand of the system, and the energy storage device provides 23.77% and 18.58% spinning reserve at the peak of non‐load, respectively, which is similar to the research results of Chiang et al (2017), 20 indicating that the algorithm proposed in this study is crucial in the smart grid operation of energy storage device, which greatly reduces the pressure of the generator set to provide spinning reserve, and indirectly increases the safety and overall service life of the generator set.…”

Section: Discussionsupporting

confidence: 87%

Adoption of distributed algorithm under alternating direction method of multipliers in energy management of smart grid

Liu

2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

This study explores the application of alternating direction method of multipliers (ADMM) in dynamic unit load energy distribution of smart grid. Firstly, the dynamic unit load energy distribution is transformed into a convex optimization based on the second-order continuous differentiable convex function. Then, a binary algorithm of distributed algorithm is constructed based on the ADMM, and energy storage devices are added to the grid nodes. Finally, Lagrange relaxation method (S1) and collaborative distributed algorithm (S2) are introduced for simulation. The results show that the original residuals and dual residuals of the proposed algorithm, S1 and S2, converge after 20, 35, and 30 iterations, respectively. The total output power of generator sets and energy storage device of the algorithm in the study is always slightly higher than the total load demand, whereas S1 and S2 are the opposite. The total spinning reserve of generator sets and energy storage device of the proposed algorithm is always slightly higher than the total spinning reserve demand, and the energy storage device provides 50.40% spinning reserve at the peak of nonload. However, the energy storage devices of S1 and S2 algorithms provide 23.77% and 18.58% spinning reserve at the peak of non-load, respectively. In conclusion, the distributed binary algorithm based on ADMM has good convergence. After 20 iterations, the original and dual residuals can converge to near 0, which can rationalize the energy scheduling of smart grid. The energy storage device provides 50.40% of the alternate reserve at the peak of non-load, which realizes the energy reselling and spinning reserve across time periods, and can increase the operation stability of the generator set. K E Y W O R D Salternating direction method of multipliers, dynamic unit load energy distribution, second-order continuous differentiable convex function, smart grids, total output power

show abstract

Section: Discussionsupporting

confidence: 87%

Adoption of distributed algorithm under alternating direction method of multipliers in energy management of smart grid

Liu

2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…The reasonable application of the lithium battery pack requires the online power state evaluation to judge whether it is safe qualitatively, which provides a reference value as a basis for the control decision-making purpose of its safety management [16]. The internal parameters in the lithium battery packs cannot be detected online, such as electrolyte concentration [17], positive-negative materials and diaphragm micropore changes [18]. The parameters such as ohmic internal resistance [19], polarization resistance and polarization capacitance in the equivalent circuit model also need to be calculated indirectly through offline experiments [20].…”

Section: Introductionmentioning

confidence: 99%

A novel power state evaluation method for the lithium battery packs based on the improved external measurable parameter coupling model

Wang

Stroe

Fernandez

et al. 2020

Journal of Cleaner Production

View full text Add to dashboard Cite

The power state evaluation plays a decisive influence on the safety implication of the lithium battery packs, and there is no effective online evaluation method so far due to the imbalance phenomenon among the internal connected battery cells, which cannot be abstained by the advancement of the materials and techniques. A novel power state description method is proposed in this paper by investigating the improved external parameter coupling treatment, in which the mutual relationship description is conducted by the parameter information feature decomposition together with the Bayesian sequential decision algorithm. The complicated power state evaluation model constructing problem of the coupling relationship decomposition is solved by investigating the non-convex optimization under complex working conditions for the lithium battery packs. The evidence combination is realized by introducing the information fusion strategy, according to which the multi criteria decision is realized by using the evidence theory. As can be seen from the experimental results, the voltage difference is within 10 mV in both of the first phase and the second phase, which increases rapidly in the third phase and reaches a maximum of 120mV. Meanwhile, its power state evaluation accuracy is 95.00% and has a good output voltage tracking effect in the complex working conditions. The power state evaluation problem can be solved by the proposed model constructing method, which is suitable for the complex battery cell combination structures and environment influences, realizing the reliable and hierarchical power state evaluation of the lithium battery packs. It provides a safety reference value and the energy management basis for the reliable power supply in the cleaner production of the power lithium battery packs.

show abstract

“…For retarding the aging of RLIB, Battery management system (BMS) with online monitoring functions, i.e. DC internal resistance (IR) and open-circuit voltage (OCV) is proposed (Chiang et al 2017(Chiang et al , 2019. ECM (equivalent circuit model) are generally adopted in dynamic system and applications of battery (Chiang et al 2011;Pei et al 2014;Feng et al 2014;Plett et al 2004;Xiong et al 2013;Li et al 2015).…”

Section: Introductionmentioning

confidence: 99%

“…The algorithm implemented in BMS aims at estimating the life cycle and remained capacity of new battery. A simple circuit by using ultracapacitor (UC) is reported in research (Chiang et al 2017). This converterless parallel circuit of BMS performs active control of RLIB by applying UC.…”

Section: Introductionmentioning

confidence: 99%

Development of Life-cycle Detection and Extending Function for Reusing Automotive Lithium-ion Battery – Verified in 52V LiMnNiCoO2 Platform

Sean

Pacheco

2020

Preprint

Self Cite

View full text Add to dashboard Cite

For reusing automotive lithium-ion battery, an in-house battery management system is developed. To overcome the issues of life cycle and capacity of reused battery, an online function of estimating battery’s internal resistance and open-circuit voltage based on adaptive control theory are applied for monitoring life cycle and remained capacity of battery pack simultaneously. Furthermore, ultracapacitor is integrated in management system for sharing peak current to prolong life span of reused battery pack. The discharging ratio of ultracapacitor is adjusted manually under Pulse-Width-Modulation signal in battery management system. In case study in 52V LiMnNiCoO2 platform, results of estimated open-circuit voltage and internal resistances converge into stable values within 600(s). These two parameters provide precise estimation for electrical capacity and life cycle. It also shows constrained voltage drop both in the cases of 25% to 75% of ultracapacitors discharging ratio compared with single battery. Consequently, the Life-cycle detection and extending functions integrated in battery management system as a total solution for reused battery are established and verified.

show abstract

Development of a converterless energy management system for reusing automotive lithium-ion battery applied in smart-grid balancing

Cited by 36 publications

References 18 publications

Adoption of distributed algorithm under alternating direction method of multipliers in energy management of smart grid

Adoption of distributed algorithm under alternating direction method of multipliers in energy management of smart grid

A novel power state evaluation method for the lithium battery packs based on the improved external measurable parameter coupling model

Development of Life-cycle Detection and Extending Function for Reusing Automotive Lithium-ion Battery – Verified in 52V LiMnNiCoO2 Platform

Contact Info

Product

Resources

About