Energy efficiency of Li-ion battery packs re-used in stationary power applications

Ahmadi, Leila; Fowler, Michael; Young, Steven B.; Fraser, Roydon; Gaffney, Ben; Walker, Sean B.

doi:10.1016/j.seta.2014.06.006

Cited by 112 publications

(90 citation statements)

References 32 publications

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“…This process was first proposed by Cready, Lippert, Pihl, Weinstock, Symons and Jungst (2003). It has more energy and work demand than the direct battery reuse, but it offers better adapted second life batteries (Ahmadi, Fowler, Young, Fraser, Gaffney & Walker, 2014).…”

Section: Remanufacturing Processesmentioning

confidence: 99%

Electric vehicle battery reuse: Preparing for a second life

Casals

García

Oliver

2017

JIEM

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Abstract:Purpose: On pursue of economic revenue, the second life of electric vehicle batteries is closer to reality. Common electric vehicles reach the end of life when their batteries loss between a 20 or 30% of its capacity. However, battery technology is evolving fast and the next generation of electric vehicles will have between 300 and 400 km range. This study analyzes different End of Life scenarios according to battery capacity and their possible second life's opportunities.Additionally, an analysis of the electric vehicle market, EV manufacturers and environmental impact defines a possible location for battery repurposing or remanufacturing plants.Design/methodology/approach: Using the center of mass equation taking 3 parameters: electric vehicle market, manufacturers and environmental impact this study suggests a location to settle a battery repurposing plant from a logistic and environmental perspective. This paper presents several possible applications and remanufacture processes of EV batteries according to the state of health after their collection, analyzing both the direct reuse of the battery and the module dismantling strategy. Findings:The study presents that Germany seems a good location to build a battery repurposing plant because of its closeness to EV manufacturers and the potential European EV markets, observing a strong relation between the EV market share and the income per capita.9% of the batteries may be send back to an EV as reposition battery, 70% will be prepared for stationary or high capacity installations such as grid services, residential use, Hybrid trucks or -266-Journal of Industrial Engineering and Management -https://doi.org/10.3926/jiem.2009 electric boats. Finally, the remaining 20% is to be dismantled into modules or cells for smaller applications, such as bicycles or assisting robots.Originality/value: Most of studies related to the EV battery reuse take for granted that they will all have an 80% of its capacity. This study analyzes and proposes a distribution of battery reception and presents different 2 nd life alternatives according to their state of health.

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Section: Remanufacturing Processesmentioning

confidence: 99%

Electric vehicle battery reuse: Preparing for a second life

Casals

García

Oliver

2017

JIEM

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“…Beverungen et al (2016) identified and validated with experts the functional and non-functional requirements for repurposed batteries from EV to stationary applications. Based on a battery expert interview and literature (Ahmadi et al 2014;Bauer et al 2016;Beverungen et al 2016), the repurposing process seems to include the same steps as reuse strategies: inspection and sorting, cleaning, dis-/re-assembly, storage, repurposing operations and testing. The repurposing step would mainly rely on reconfiguring the different components and sub-assemblies of the products and include a few product developments in order to then fulfil new requirements or connect the components in the new fashion.…”

Section: Core Collectionmentioning

confidence: 99%

Design for High Added-Value End-of-Life Strategies

Bauer

Brissaud

Zwolinski

2017

Sustainable Manufacturing

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Sustainable manufacturing is a rising issue. Ensuring both consumer satisfaction and minimal environmental impact is very challenging. In that whole process, it is customary to say that the design stage determines 80 % of the future environmental impact. One way to contain this impact at an acceptable level is to manage the products' end-of-life from the design activities. This chapter points out product reuse strategies-i.e. direct reuse and remanufacturing-aiming at conserving the added-value of used products as much as possible into new products. The first contribution attempts to provide a state-of-the-art of design for these high added-value end-of-life strategies. Direct reuse and remanufacturing are thus analysed and the principal design guidelines are furthermore given, classified according to three dimensions: product, process and business model. This chapter then contributes to enlarging the spectrum of reuse strategies, presenting an innovative end-of-life strategy: repurposing. It consists of reusing products in other applications after transformations. The main challenges of such a strategy will be discussed.

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“…In modern railway applications, energy efficiency is also an important aspect used to estimate the performance of lithium ion batteries in recent studies [23][24][25][26], since higher efficiency means more energy savings and reduced costs. Determining how to optimize the battery usage strategy by improving the energy efficiency during the working process is the key issue for managing energy usage in modern railway applications.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Learning-Based Continuous-Time Estimation and Simulation Method for Energy Efficiency and Coulombic Efficiency of Lithium Ion Batteries

et al. 2017

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Lithium ion (Li-ion) batteries work as the basic energy storage components in modern railway systems, hence estimating and improving battery efficiency is a critical issue in optimizing the energy usage strategy. However, it is difficult to estimate the efficiency of lithium ion batteries accurately since it varies continuously under working conditions and is unmeasurable via experiments. This paper offers a learning-based simulation method that employs experimental data to estimate the continuous-time energy efficiency and coulombic efficiency of lithium ion batteries, taking lithium titanate batteries as an example. The state of charge (SOC) regions and discharge current rates are considered as the main variables that may affect the efficiencies. Over eight million empirical datasets are collected during a series of experiments performed to investigate the efficiency variation. A back propagation (BP) neural network efficiency estimation and simulation model is proposed to estimate the continuous-time energy efficiency and coulombic efficiency. The empirical data collected in the experiments are used to train the BP network model, which reveals a test error of 10 −4 . With the input of continuous SOC regions and discharge currents, continuous-time efficiency can be estimated by the trained BP network model. The estimated and simulated result is proven to be consistent with the experimental results.

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Energy efficiency of Li-ion battery packs re-used in stationary power applications

Cited by 112 publications

References 32 publications

Electric vehicle battery reuse: Preparing for a second life

Electric vehicle battery reuse: Preparing for a second life

Design for High Added-Value End-of-Life Strategies

A Data-Driven Learning-Based Continuous-Time Estimation and Simulation Method for Energy Efficiency and Coulombic Efficiency of Lithium Ion Batteries

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