In-Service EV Battery Life Extension Through Feasible Remanufacturing

Abstract

While a number of publications have addressed the high-level requirements of remanufacturing to ensure its commercial and environmental sustainability, considerably less attention has been given to the technical data and associated test strategies needed for any evidence-based decision as to whether a vehicle energy storage system should be remanufactured - extending its in-vehicle life, redeployed for second-life (such as domestic or grid storage) or decommissioned for recycling. The aim of this paper is to critically review the strategic requirements for data at the different stages of the battery value-chain that is pertinent to an Electric Vehicle (EV) battery remanufacturing strategy.

Discussed within the paper is the derivation of a feasible remanufacturing test strategy for the vehicle battery system. Experimental results are presented that explore the trade-off between test accuracy as a function of key variables such as the ambient temperature at which the measurements are taken, the rate at which electrical current is used to charge/discharge the battery and the relaxation time allowed for the battery to equilibrate before the test is commenced. It is highlighted that the cost and environmental impact of remanufacturing EV battery systems relies heavily on the availability of a viable test strategy. Initial findings from the research are presented and testing on a 20 Ah pouch cell highlights that the variation in discharge capacity due to different temperatures can result in circa: 14% under-estimation. Also, waiting times between test periods (as defined within the best practice standards) can be reduced for different cells to improve testing time efficiency.

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16SDP-0009
In-Service EV Battery Life Extension Through
Feasible Remanufacturing
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Abstract
While a number of publications have addressed the high-level
requirements of remanufacturing to ensure its commercial and
environmental sustainability, considerably less attention has been
given to the technical data and associated test strategies needed for
any evidence-based decision as to whether a vehicle energy storage
system should be remanufactured – extending its in-vehicle life, re-
deployed for second-life (such as domestic or grid storage) or
decommissioned for recycling. The aim of this paper is to critically
review the strategic requirements for data at the different stages of
the battery value-chain that is pertinent to an Electric Vehicle (EV)
battery remanufacturing strategy.
Discussed within the paper is the derivation of a feasible
remanufacturing test strategy for the vehicle battery system.
Experimental results are presented that explore the trade-off between
test accuracy as a function of key variables such as the ambient
temperature at which the measurements are taken, the rate at which
electrical current is used to charge/discharge the battery and the
relaxation time allowed for the battery to equilibrate before the test is
commenced. It is highlighted that the cost and environmental impact
of remanufacturing EV battery systems relies heavily on the
availability of a viable test strategy. Initial findings from the research
are presented and testing on a 20 Ah pouch cell highlights that the
variation in discharge capacity due to different temperatures can
result in circa: 14% under-estimation. Also, waiting times between
test periods (as defined within the best practice standards) can be
reduced for different cells to improve testing time efficiency.
Introduction
The main objective of this paper is to highlight the need to define a
testing strategy for Electric Vehicle (EV) batteries that includes Zero-
Emission Vehicles (ZEVs) (specifically battery electric vehicles
(BEVs)) and hybrid EVs (HEVs) at the design stage to enable
feasible remanufacturing. HEVs are classified as mild hybrid, passive
or assisted hybrid and full hybrid [1]. If the battery can be charged
with an external power source it is referred to as a plug-in HEV
(PHEV). For the purpose of this paper the term EV will be used to
include BEVs and HEVs that both contains an energy storage system
(ESS) that could potentially be remanufactured. Before the feasible
strategy is discussed, the motivation behind the growing adoption of
EVs and the intensified focus on remanufacturing will be reviewed
first.
As a result of a worldwide effort to reduce CO2 emissions [2], the
European Union (EU) introduced CO2 emission standards on
passenger cars with a 95 gCO2.km-1 target set for 2020 [3]. The
regulation of vehicle emissions is due to the fact that 29% of
Greenhouse Gas (GHG) emissions comprises of transport emissions
[4] and the passenger car contributes 12% towards the total transport
emissions [5]. One way of reducing CO2 emissions in passenger cars
that has been under increasing investigation in recent years is the
introduction of ZEVs into the market [5,6]. The two mainstream
ZEV vehicle technologies are BEV and hydrogen fuel cell electric
vehicles (FCEV) [8]. There is a clear financial benefit associated with
BEVs compared to HEVs [9] and a greater reduction in CO2
emissions that can be achieved with BEVs [10].
Uptake of EVs is predicated to be up to 15% of new cars sold in 2025
in the EU market, resulting in 20 million EVs [11]. However, this
rate of EV adoption is not high enough if the EU GHG 2050
reduction target of 60% is to be achieved [12].
The preferred battery of choice for use in EVs is Lithium-ion
batteries (LiBs) [13] due to their high energy density, low weight and
long lifespan [14]. One major barrier to the uptake of EVs powered
by LiBs is the higher initial investment compared to conventional
internal combustion engines (ICEs) [15]. The EV battery is mainly
responsible for the high initial cost [16]. However, LiB pack prices
are reducing from the current £395 per kilowatt hour (kWh) to a
predicted £106 per KWh in 2025 [17]. Due to the slowly increasing
demand for EVs [18] partly caused by reducing LiB prices and the
End-of-Life (EoL) legislation, the EoL strategy of EVs and the
battery packs they contain require careful consideration at the design
stage of the vehicle. The EoL legislation that is directly applicable to
EVs are the European Parliament EoL vehicle directive 2000/53/EC
also known as the ELV directive [19] which aims to prevent waste
from vehicles at the recovery stage and the European battery directive
which prohibits disposal of EV batteries (classed as industrial
batteries) by means of landfill or incineration [20]. Both the ELV
directive and battery vehicle directive also represents a move to
Extended Producer Responsibility (EPR) to stimulate sustainable life
cycle management of products [21]. Under the EPR the vehicle
manufacturers are financially responsible for the recycling costs of
the vehicles and the batteries. A LiB is seen to be at EoL when it
reaches 80% of the capacity compared to new [21–24] and still have

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considerable inherent value [24–26]. An EV battery lifespan is
believed to be 8 to 10 years [12,27,28]. Traditional vehicle lifespan is
considered to be between 10 and 16 years [30-32]. This mismatch
between vehicle and battery life creates the opportunity to keep the
LiB in use for longer. Extending the lifetime of the LiB will also have
an environmental benefit as it will reduce the need for material
production that causes environmental pollution [15]. This can lead to
significant reduction in environmental pollution due to the EV battery
production process contributing significantly to the CO2 emissions of
a EV’s total lifetime emissions in its lifecycle [33,34].
The EPR, the need for EV battery lifetime extension and above
mentioned environmental benefit embodies some of the key
principles of a circular economy. A circular economy (Figure 1) is an
industrial system that is restorative or regenerative by design and
aims to move away from traditional linear consumption (make, use,
dispose) to a circular, closed looped system. Adopting this system has
economic, environmental and social benefits and strives to retain key
resources within the supply chain for longer, extracting maximum
value from them before regenerating products and materials at the
end of their service life [34]. Benefits includes an estimated annual
saving of between €465 - 565 billion in the EU if a circular economy
was achieved in relevant manufacturing sectors [35]. Included in this
is the automotive industry, which is showing strongly increased
momentum in the EV market [36].
Figure 1. The circular economy.
Before an effective EoL option can be chosen all other options should
be considered first. The EoL routes include reuse or repurposing [37],
recycling [38] and remanufacturing [39]. Recycling of EoL batteries
are not the ideal option since only 42% of EV batteries (by weight) is
currently being recycled and does not include high value materials
such as lithium [13]. Recycling also destroys the inherent value of the
cells at 80% capacity. The other EoL option is to re-use the battery in
another application by repurposing the battery as a stationary Energy
Storage System (ESS). The main problem with repurposing the EV
battery is it can only be economically feasible if research and
development costs are kept to a minimum [40] compared with the
final option, namely remanufacture.
Remanufacturing is a process which can often be confused with other
EoL options such as repair, reuse and recycling [41]. This is further
complicated by the lack of a globally accepted legal definition [42].
British Standards (BS 8887) regarding Design for Remanufacture
(DfR) do exist [43], but only go as far as defining each process step.
There is also a mismatch between defined automotive
remanufacturing and remanufacturing for EV batteries. This is
mainly due to the fact that current remanufacturing practices and
standards are all aimed at mechanical systems and is reflected in
Publicly Available Specifications (PAS) on remanufactured
automotive parts specification released at the end of 2014 [44]. Most
remanufacture definitions in the literature follow the same train of
thought regarding the quality of the final product, which should be to
at least the same standard and specification as the original product
[46,47]. Other remanufacture definitions also specify that the
remanufactured product must be given a warranty of the same length
of a newly manufactured product [47]. In the case of automotive
battery packs, the proposed definition of remanufacturing is given as:
“the repair and replacement of some parts to be as good as usual,
including the replacement of individual components and entire
modules” [48].
Remanufacturing is generally split into three business types, Original
Equipment Manufacturer (OEM) remanufacturing, contracted
remanufacturing and independent remanufacturing. With the first
two, the OEM maintains some control over remanufacturing
operations, which support better control over profit margins and
improve product remanufacturability due to more information being
shared. With Independent Remanufacturers (IRs), it is unlikely that
the OEM is deeply involved and therefore increasing product
remanufacturability may prove more difficult [49].
Remanufacturing practices can be found worldwide in various
industries and sectors, including automotive parts, electrical home
appliances, personal computers, mobile phones, photocopiers, single-
-use cameras, cathode ray tubes, automatic teller machines, vending
machines, construction machineries, industrial robots, medical
equipment, heavy-duty engines and aircraft parts [50]. The USA has
emerged as a leader in terms of producing, consuming and exporting
remanufactured goods, with £28 billion ($43 billion) produced in
2011, accounting for 2% of sales for all manufactured goods [42].
In [51], Lund created a database of all the remanufacturers in North
America and categorized the remanufacturers by type. Lund’s results
show that there are 121 different categories and over 8,000 individual
remanufacturing establishments in North America. Of these
establishments, the most popular were companies that remanufacture
motors, generators, pumps, automotive parts and photographic
equipment. Various government bodies and consortiums also exist to
help facilitate and promote remanufacturing and are shown in Table
1.
Table 1. Summary of remanufacturing bodies.
Body
Summary
The Centre for
Remanufacturing and Reuse
(CRR) [52]
Promote remanufacturing, reuse
and reconditioning across
various business sectors.
Provide paid services for
businesses wishing to
implement remanufacturing and
reuse

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Resource Conservative
Manufacturing (ResCoM) [53]
A European Commission
project working on the
development of closed-loop
product systems, focusing on
remanufacturing, reuse and
multiple lifecycles.
Developing Resource Efficient
Business Models (REBus) [54]
A Wrap [55] lead initiative that
aims to raise awareness of
remanufacturing across the EU.
A collaboration between
several insinuations and
provides support for companies
wishing to switch to more
resource efficient business
models, which remanufacturing
will play a vital role in.
Project Remanufacturing
Service System (PREMANUS)
[56]
Combines information and
product services in order to
provide decision making
software based on a particular
product’s lifecycle.
Centres of excellence
Include: Rochester Institute of
Technology [57], University of
Strachlyde [58] and The
Advanced Remanufacturing
and Technology Centre in
Singapore [59].
In [60] several design factors were outlined by W. Ijomah that can
affect product remanufacturability, such as assembly type, product
complexity, materials, design cycle, product disassembly. The
product complexity design features can also be related to testing as
well as other stages of remanufacture.
State-of-the-art remanufacturing in the automotive industry is an
established practice with regards to mechanical components such as
engines, gearboxes and alternators. Examples of this are
demonstrated by Volvo Construction Equipment (Volvo CE) [61] and
Caterpillar [62].
Volvo CE manufactures construction equipment for 150 countries
worldwide and claims that their remanufacturing programme offers
the best value to its customers. Unlike Thermagroup Limited, which
is an independent retailer offering remanufactured air conditioning
chiller units and compressors and began to consider remanufacturing
once the products were already in use, Volvo CE began
remanufacturing to keep pace with competitors [61]. Volvo CE gives
all remanufactured products the same performance, service life and
warranty as a new one [61]. During the remanufacturing process, new
technologies and upgrades are often introduced resulting in an
upward remanufactured product which is an improvement on the
original [63].
Another influential company in the automotive remanufacturing
industry namely Caterpillar, manufactures construction equipment
and has identified remanufacturing as key in maintaining a
sustainable business. Caterpillar have a dedicated section of the
business called ‘Cat Reman’ claiming to be the world’s leading
remanufacturing company [49]. Whilst they provide some detail on
their remanufacturing process it is still limited.
At Caterpillar, when a remanufactured product such as an engine is
purchased, the price includes a core deposit as an incentive. The
deposit is returned to the customer when they return the product (or
core) that is being replaced, ensuring a steady stream of core supply
to keep the remanufacturing loop active. The cores are then shipped
to different remanufacturing plants globally and the generic
remanufacturing process described later in this section is followed
[62]. Caterpillar is also a prime example of remanufacturing at the
design stage creating benefits further down the line. The engine
blocks are manufactured with a removable sleeve in the cylinder
bore, which means that when the component is recovered it can be
removed and replaced. This was traditionally done by re--boring the
engine cylinder, but could only be carried out three times before
detrimentally effected product quality. They also implement additive
manufacturing techniques by spraying metal onto the cylinder bores
during reconditioning [64].
Research streamlining the traditional ICE remanufacture process in
the automotive industry has been already been performed [65]. In
terms of the remanufacturing process for engines, the products are
first inspected to determine suitability for remanufacture, before
moving to the cleaning area. This is deemed necessary as it will
highlight any faults that may have been covered up or caused by
grease and dirt and occurs a number of times throughout the process.
Traditional engine cleaning methods will not be suitable for use in
EV manufacturing because many of the components within the pack
will be sensitive to liquids and temperatures outside of certain
parameters. This could be problematic if there has been a leak of
coolant or electrolyte within the pack. An effective cleaning method,
which does damage sensitive components within the pack, will need
to be established for scenarios such as this.
The dismantling stage is carried out and in this case, every
component in the engine is fully dismantled and high stress parts, for
example, pistons are automatically discarded. This is most likely a
reliability issue, the level of stress the pistons have been under is
unknown and so replacing them all can mitigate the risk of failure.
The dismantling stage for an EV battery will be more complex
compared to engine disassembly due to the safety concerns
associated with energy storage devices such as the risk of injury due
to electric shock. Safe systems of work will have to be developed and
implemented for working with EV LiBs in the dismantling stage.
Other major components such as camshafts are sent to different areas
for testing and if possible are machined back to OEM specifications.
The engine block is tested for cracks before being sent to the
Computer Numerical Control (CNC) machine to allow a tight fit for
pistons sleeves whilst other engine parts undergo similar processes in
order to regain original specification. Testing for an EV LiB needs
special consideration and is not as streamlined as current engine
remanufacture testing procedures.
The parts are then reassembled using the same techniques as original
engine assembly and finally tested. Throughout the process various
tools, gauges and machines are used to ensure precision. In addition,
each workstation contains a computer detailing information on every
part and process within the factory so measurements can be stored
and progress tracked [66]. The tracking and information management
developed for engine remanufacture could be used and implemented
in EV LiB remanufacturing.

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Traditional automotive starter batteries have lead–acid chemistries
and extensive research activities on dealing with and processing these
type of batteries has already been performed [55,56,62-64]. Due to
the different storage conditions of lead acid batteries (with a high
SoC, low temperature and ventilated area) and LiBs (with a low SoC
and low temperature), the difference in chemistry and form factor, the
remanufacturing process has to be revised and adapted for a LiB.
Table 2. Engine [62], PlayStation [71] and Photocopier [72] of
remanufacturing comparison.
There are limited examples within the literature of electrical products
that have detailed remanufacturing process information. Examples of
existing case studies for electrical product remanufacture include the
Sony PlayStation [50,65] and photocopiers [72]. However, whilst
there is information available on the specific remanufacturing
processes for mechanical parts, as discussed above at the hand of the
Volvo and Caterpillar examples, there is less information available on
the remanufacture of electrical components where they exist.
However, these examples could still provide a useful basis to build a
battery pack remanufacturing process on.
A comparison between the remanufacturing processes of automotive
engines [62], the Sony PlayStation [71] and photocopiers [72] is
shown in Table 2. As demonstrated by Table 2, it can be difficult to
compare and contrast the remanufacturing process for different
products. However, some similarities can be seen in the techniques
and technologies used during some process stages. The order in
which each stage occurs can differ, with testing and cleaning taking
place at various stages of the different processes. Additionally, from
the limited information available, it is clear that the technologies and
techniques utilised during cleaning, reconditioning and testing differ
significantly. However, similarities in techniques can be seen
between the PlayStation [71] and Photocopier [72] cleaning process,
most likely due to their electrical components and the absence of hard
to remove soils. Additionally, whilst both the engine [62] and
photocopier [72] require full disassembly, it is suggested for the
PlayStation [71] that full disassembly may not be required, depending
on the fault type.
The importance of remanufacturing is demonstrated by the
remanufacturing market size, which is estimated to be between 6.3 to
7.7 billion pounds in Europe [73] and 70 billion pounds globally [74].
Extending remanufacturing in Europe could create 300,000 skilled
jobs to local communities, demonstrating social benefits [75].
Additionally, the environmental benefits of remanufacturing in the
UK have so far included avoiding the use of 270,000 tonnes of raw
material and the release of 800,000 tonnes of CO2 emissions [49].
The CO2 emissions related to the manufacture of a LiB has been
calculated to be approximately 75 kg.CO2.kWh-1 [76]. To put this in
perspective, a Nissan Leaf battery pack for example, is estimated to
be 24 kWh in size [77] which translates to 1,800 kg of CO2 emissions
for every Nissan Leaf battery pack manufactured. With battery packs
for Plug-in PHEVs and pure EVs ranging from 10 -50 kWh in size
[78], it is clear that an efficient remanufacturing process for battery
packs could also bring significant environmental benefits through
CO2 avoidance.
Thus when considering the vehicle EoL and battery directive
legislation, the lifetime mismatch between vehicle and battery pack,
and the options of reusing, remanufacturing or recycling EoL
strategies, it is clear that remanufacturing is an EoL strategy that can
address all these issues in the majority of EoL cases. EV battery pack
remanufacturing can help to avoid additional recycling cost for
producers by keeping the same battery pack in use for longer,
avoiding replacement with a new one during vehicle life which will
also need to be recycled at the EoL, potentially incurring up to double
the recycling costs. Remanufacturing will also address the lifetime
mismatch between vehicle life and battery life, partially removing the
barrier of high initial cost by utilising the inherent EoL value in the
first life cycle of the vehicle.
The generic remanufacturing process includes inspection,
disassembly, part replacement/refurbishment, cleaning, reassembly
and testing [79]. Whilst there are examples of remanufacturing
processes and tools to help effectively assess and implement
remanufacturing [73-75], there is currently no evidence in literature
of the remanufacturing process for a complete EV battery pack. In
order to ensure the feasibility and quality of a remanufactured battery
pack, there will be key points within this generic remanufacture
process that will have to be assessed and refined for adoption in a
battery pack remanufacturing scenario. Also, the state of the art
remanufacturing processes for automotive parts discussed earlier
cannot be directly applied to the EV LiB pack due to its
electrochemical nature which needs special consideration when it
comes to safe handling, storage and evaluation during the
remanufacturing process. One of these key points is testing at the
inspection stage which is of vital importance when working with
energy storage devices compared to purely mechanical devices.
Because testing forms part of inspection within the remanufacture
process and the remanufacture process forms just a part of the reverse
logistics chain which fits within the circular economy model, testing
has a direct influence on EoL decisions which can directly influence
the feasibility of the remanufacture process. The remanufacture

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feasibility feeds directly into the economic and environmental
sustainability of the circular economy.
The aim of this paper is to highlight the importance of developing a
feasible testing strategy at the design stage of the EV battery pack
when considering remanufacturing as an EoL option. The paper
shows the complexity of an EV battery pack to show the multi-
faceted testing strategy needed. The paper will focus on cell level
testing, defining a feasible test strategy for the reverse logistics chain
and will critically review the capacity testing standards. The paper
will identify key variables that need to be investigated further in
order to achieve a feasible capacity test.
EV battery systems are discussed and current EV battery testing
standards are outlined. A review of the reverse logistics chain of the
EV battery for remanufacturing is also included. Feasible
remanufacturing with respect to battery pack testing is defined and
highlighted key variables such as C-rate, temperature and wait times.
This paper also highlights how the key variables can effectively be
taken into consideration within a remanufacturing test strategy. The
final section of this paper presents data on the variation of battery
capacity measurements with respect to different variables.
This paper is structured as follows: The first section is a discussion
about the EV battery packs currently in use. The second section
discusses the reverse logistics chain of the EV battery for
remanufacturing. The third section critically reviews the current EV
battery testing standards. The fourth section introduces the feasible
remanufacturing strategy and feasible testing strategy and illustrates
how the two strategies relate, highlighting the importance of testing.
This is followed by the results section which presents the variation in
capacity tests under various temperature, wait time and C-rate
conditions. Finally conclusions and further research are presented.
EV Battery Pack
EV pack design varies significantly across different automotive pack
manufacturers in terms of chemistry, form factor and cooling
strategy. Various chemistries including Lithium Cobalt Oxide
(LiCoO2), Lithium Iron Phosphate (LiFeP04), Lithium Nickel Cobalt
Manganese (NCM - LiNixCoyMnxOZ) and Lithium Titanate Oxide
(LTO - LI4Ti5O12) are undergoing significant research and
characterisation activities. The three main form factors currently
being deployed by automotive EV pack manufacturers are the 18650
cylindrical cell used in the Tesla model S [82], the pouch type cells
used in the Nissan Leaf [83] and the prismatic cell used in the
Mitsubishi i-MiEV [82]. The parts within an EV battery pack can
generally be split into four high levels: sub-assemblies, electrical
components, structural components and the thermal management
system. The sub-assemblies (or ‘sub-packs’) contain a number of
modules, which in turn contain a number of cells.
Outside of the sub-assemblies the pack also contains other electrical
components such as the Battery Management System (BMS), High
Voltage (HV) wiring and various power distribution equipment. In
order to keep all components secured, structural components are
required throughout the pack, including enclosures and supports.
Finally, a battery pack may also contain a thermal management
system to keep components, particularly the modules and cells,
within certain temperature parameters. Thermal management systems
include liquid-cooled or air-cooled types.
To illustrate the complexity of an EV battery pack currently being
deployed, an overview of the contents of a commercially available
Nissan Leaf is presented in Table 3. The 2014 Nissan Leaf with a
pack energy of 24 kWh has a reported range of 73 miles over a
United States environmental protection agency (EPA) cycle [84] and
124 miles over a New European Drive Cycle (NEDC) [85]. The
complete battery pack contains 48 battery modules, each containing 4
Lithium-ion (Li-ion) cells arranged in a 2-parallel 2-series (2P2S)
arrangement. The pack does not have an active cooling system but
has an electrical element to warm the Li-ion cells during cold
temperature operation. The pack is attached to the vehicle chassis
with 20 mechanical bolts. The modules can be accessed by removing
the pack lid held on by 20 bolts and glued along all the edges of the
pack. Once the pack is opened, modules can be assessed for repair
and/or remanufacturing activities. Within the pack a total of 376
fasteners including mechanical screws and bolts are employed to join
the various modules, cells and electrical interfaces [86]. No
mechanical welding or adhesives were employed within the pack
assembly potentially simplifying any future remanufacturing activity.
Table 3. Overview of the Nissan Leaf battery system.
To ensure the optimum EoL strategy in terms of environmental
impact and financial cost is identified, a clear understanding of the
factors that degrade the cell capacity is needed. Several studies
highlight the importance of cell operating temperature and energy
throughput resulting in an increase in impedance and a decrease in
capacity [64–66]. Based upon a better understanding of battery
degradation, the decision making model in [48] highlighting different
EoL scenarios mapped to the EoL options (discussed in the
introduction) can be discussed. The model identifies remanufacturing
as the optimal choice for EoL for a cell with a capacity between 80-
100%. For cell with a retained capacity of between 45% and 80%, re-
use within grid storage is identified as the best EoL option. Below the
45% threshold, material recovery through recycling will yield
greatest economic benefit.
The demonstrated high level of complexity for EV battery systems
increases the importance of considering the remanufacturing process
at the design stage, rather than an afterthought.
EV Battery Reverse Logistics Chain for
Remanufacturing
In addition to the EoL scenario that encompasses the EV and battery

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system as a whole, another important consideration is how to manage
premature battery EoL caused by an individual battery cell within a
module that has degraded within the complete assembly. When faced
with a failed battery in a customer’s vehicle, the default position for
many automotive manufacturers will be to replace the complete
battery assembly. Some of the automotive manufacturers have started
to investigate re-use as an EoL option (as shown in the EoL options
summary for mainstream EV manufacturers in Table 4).
Table 4. Summary of mainstream EV manufacturers preferred EoL options.
The long term sustainability of the approach to replace the complete
assembly is unclear given the financial cost of replacing the battery
system like the one used in the Nissan leaf is circa £5000 [90], the
environmental impact associated with its initial manufacture and the
cost of recycling incurred by the battery pack manufacturer. This
scenario creates the ideal opportunity for remanufacturing to address
the long term financial and environmental sustainability. However
before the concept of feasible remanufacturing can be discussed the
reverse logistics chain with regards to remanufacturing needs to be
investigated. The full reverse logistics chain highlighting all the
stakeholders will not be discussed here, as most of the details are out
of the scope of this paper.
For the purpose of this investigation only the high level lifecycle of
the EV battery pack (shown in Figure 2) and the logistics chain
(shown in Figure 3) for the remanufacturing is discussed.
For the lifecycle in this study the assumption is made that the default
option for the EoL strategy will be remanufacturing at pack level.
Depending on reverse logistics constraints for example Li-ion battery
transportation legislation, particularly Li-ion batteries classed as
damage or defective under the Carriage of Dangerous Goods (ADR)
act [91], module or cell level re manufacturing might need to be
employed.
The employment of a deeper level of remanufacturing will also be
determined by the ability to diagnose and identify premature EoL
battery issues at the various stakeholders described in Figure 2. The
stakeholders involved at the different stages in the battery pack’s
lifecycle are identified as: pack manufacturer, vehicle manufacturer,
dealer and owner. Throughout the lifecycle each stage requires
testing of the battery cell/modules/pack to be able to verify and
identify the health and state of the Li-ion battery.
The tests will have varying mechanical testing requirements at the
different stages within the lifecycle but will have the same
electrochemical requirements, namely the immediate energy state of
the cell and the health of the cell. The term State-of-Charge (SoC),
which is a measure of the fraction of energy contained in the cell as a
percentage of the total energy capacity of the cell, is used when
referring to the energy state of the cell. The health of the battery
measurement is referred to as the State-of-Health (SoH) and
determines the current condition compared to when the battery was
new. The measures that will be used to determine the SoH of the cell
will be discussed in the feasible remanufacturing and testing strategy
section. The main difference for the electrochemical testing
requirements between the stages is the accuracy and detail level of
the data required from the tests, for evaluation and decision making
purposes. For example, at the vehicle owner stage the information
from the Battery Management System (BMS) will be sufficient for
the driver to make decisions about range and capacity.
Figure 2. High level EV battery lifecycle.
When an EoL pack is fit for remanufacture, BMS data that includes
measurements of Open Circuit voltage (OCV), current and
temperature alone will not be enough to make an informed decision.
This is due to the fact that when a battery pack enters the
remanufacturing stage, it will probably do so under one of the
following three scenarios:
 Ancillary failure (BMS, sensor, pump or contactor failed)
 Battery module/pack performance has degraded
 Damaged module/pack - EV involved in a crash
The BMS consist of hardware and software and as such is
constrained in terms of available data by both hardware and software
limitations [89]. For the ancillary failure and damaged pack scenarios
the availability of BMS data cannot be guaranteed. Also, for the
degraded performance scenario the data collected and stored on the
BMS will vary for different manufacturers and pack designs might
not be sufficient to make an informed EoL decision. Limited storage
on the BMS could also lead to some historic data being lost over the
use phase of the battery. Therefore EoL testing should have the
capability to be performed without the BMS.
EV Manufacturer
EoL options
BMW
Re-use, Recycling
Chevrolet
Re-use, Recycling
Nissan
Re-use, Recycling
Mitsubishi
Recycling
Renault
Re-use, Recycling
Tesla
Recycling
Volkswagen
Recycling

Page 7 of 15
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Figure 3. EV battery pack logistics chain for the remanufacturing stage shown
in Figure 2.
From the above discussion the need to focus on testing to verify if
remanufacturing is the best option at the EoL decision stage were
identified. Before the testing strategy can be discussed a critical
review of the current cell level test is outlined.
Current State of Testing Standards
Current testing standards for capacity measurement of Li-ion cells
(i.e. IEC-62660 and ISO-12405) only define cell-level test
requirements and if followed would require in excess of 190 hours to
complete performance tests [60,61].
For the purpose of this paper the focus is placed on capacity
measurements. In Figure 4 the capacity test durations for various
mainstream standards is shown assuming the defined C-rates are used
and recommended wait times were applied. The capacity test for a
single cell can vary from 11-75 hours.
Figure 4. Capacity test duration for various mainstream standards. Compiled
from [66, 68–70].
Such an excessive test
duration, coupled with
the expected rise in EV
sales volumes to 11
million globally by 2020
[27], would be
prohibitive for a number
of vehicle manufacturers
and specialist suppliers.
Furthermore, currently
the criteria for
determining whether a
EV LIB is fit for battery
electric vehicle use
remains unclear,
however, it is generally
accepted that once a
pack reaches 80% of its
original capacity, it is no
longer suitable for
vehicle application
without modification
[97].
In order to get a fair comparison with the standards that only defines
cell level testing, the test strategy in this paper is defined at cell level.
This test can be adopted in other areas in the value chain shown in
Figure 2 where testing needs to be performed, for example the same
test can be performed to verify the battery pack is fit for purpose at
the end of the vehicle manufacturers assembly line.
Thus it has been established through consideration of the complexity
of the EV battery pack, the reverse logistics chain highlighting the
need for testing and the current state of testing standards highlighting
excessive testing times that a robust testing strategy must be
developed to ensure feasible remanufacturing can be achieved.
Defining Feasible Remanufacturing and a
Feasible Testing Strategy
Feasible Remanufacturing
In order for remanufacturing to be an attractive EoL option it needs to
have financial and environmental benefits. However if the testing at
the different stages of the lifecycle of the EV battery is not feasible,
remanufacturing will not be a viable EoL option. Thus Feasible
Remanufacturing (FR) is governed by the remanufacturing business
model, the environmental considerations determined by the EV
battery’s Lifecycle Assessment (LCA) and Feasible Testing (FT) that
will be defined later in this section. K. Aguirre and L. Eisenhard’s
paper [98] describe the main environmental consideration identified
when considering the LCA of the EV and battery are the CO2
emissions during production and the EV use phase. The testing of the
EV battery can also make a significant contribution to the production
of CO2 emissions and since testing forms such an integral part of the
EV lifecycle it needs to be taken into consideration when defining a
feasible test strategy. Thus feasible remanufacturing is a function
( of the following:
      (1)
0
10
20
30
40
50
60
70
80
Capacity test time (hours)

Page 8 of 15
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Where, process cost in pounds sterling (£) will directly impact the
business model of remanufacturing and is defined as:
    
 (2)
Where, the cost of the test in pounds sterling (£) will be dictated by
the energy used during the testing and the duration of the test and is
defined as:
     (3)
The energy loss (in kWh) of the test can be defined as the following:
   
 (4)
Where, the energy recovered (in kWh) and put back into the grid is
dependent on the equipment used. If the equipment has the capability
to return the energy used to charge up cells back to the grid with high
efficiency the environmental impact can be reduced. For the purpose
of this study we assume no such functionality is available and
therefore all energy in testing process is lost. The energy used during
testing is defined as:
     (5)
with the temperature (in °C) being the value at which the test is
being performed. The test time (in hours) a function of
   (6)
with the C-rate representing the charge and discharge rates of the
battery cell/module/pack. Thus the test time will be dictated by the
charge and/or discharge time of the cell. The energy needed to
change the temperature of the cell from temperature 1 () to
temperature 2 () can be calculated as [99]
       (7)
with Q the energy required to change the temperature of mass ()
using the Specific Heat Capacity () of the cell. Now that the
energy used during a test can be calculated, the contribution of testing
to the environmental component of the LCA can be calculated. The
Carbon Dioxide (CO2) produced by the test is a function of
     (8)
with the grid mix representing the gCO2.kWh-1 value of the energy
from the grid that was utilized in a specific country during the test of
the cell.
Feasible Testing Strategy
In order to assess the testing in the remanufacturing stage for EoL
decision making and to determine if it is economically,
environmentally and practically feasible, a definition for FT is
needed. Thus feasible testing is defined as a function of
    (9)
with the accuracy (in %) referring to the accuracy of the test
measurements and cost of test as previously defined. The
measurement accuracy is a function of
    (10)
with the temperature the same as defined previously. The total time is
defined as
     (11)
with  the test time (in hours) as defined previously.  is the
relaxation time needed for the cell/module/pack to reach thermal
stability before a charge or discharge event.
Thus feasible testing is governed by the time the test takes to achieve
a desired accuracy for the measurement and the cost of the test. For
feasible remanufacturing of an EV battery it is not just the process
cost and environmental impact of remanufacturing that dictates if the
process is feasible but also the availability of a viable test strategy.
In order to fully investigate the SoH of a cell both the impedance and
capacity of the cell need to be investigated. The impedance and
capacity performance parameters can be traced back to previously
defined tests for Li-ion cells in international standards [66, 68]. The
link between temperature, capacity fade and impedance increase have
been established in several studies as highlighted in the introduction.
The effect of temperature on the SoH can have a negative impact for
both high and low temperatures [100]. The link between relaxation
time and capacity has also been studied [101] and shows capacity
increase with an increase in relaxation time. The link between
impedance and high temperature cycling has already been established
[102] and cell impedance increase is expected at high temperatures.
The link between low temperature and impedance also show
delivered capacity substantially reduced [103]. Considering all of the
above mentioned links between temperature, wait time, capacity and
impedance it is necessary to consider testing as a matrix shown in
Figure 5. This will allow for a comprehensive evaluation of the SoH
of a cell that will ensure feasible testing in order to support feasible
remanufacture. The impedance and capacity of cells needs to be
investigated in terms of total test time that is dictated by the C-rates
employed during testing, wait time and test temperature. The total
test time directly influences the cost of testing. Thus testing needs to
be considered as presented in Figure 5.
Figure 5. Test Matrix.

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In this work, only capacity versus time and capacity versus
temperature was considered to investigate the test accuracy during
capacity measurements.
Experimental Results
Methodology
The work that was performed included capacity measurements for
varying test temperature, C-rates and wait times with two
commercially available 20 Ah pouch cells with a LiFePO4 cathode
and LiC6 (graphite) anode. The cells were placed on purpose built
rigging and connected to cell cyclers capable of delivering sufficient
current to perform test at required C-rates. A thermal chamber was
used to ensure temperatures are maintained during testing within
±2°C of the target temperature. All cells were new and were fully
characterised using the IEC-62660 standard with the reference
capacity test comprising of a 1C charge and discharge rate with 3
hours relaxation time at 20°C. Temperature conditioning were
performed as described in the IEC-62660 standard and the range of
temperatures considered were -10°C, 0°C, 20°C, 40°C.
Thermocouples were placed on each cell in the positions shown in
Figure 6.
Figure 6. Thermocouple positions.
The T-type thermocouples had a measurement accuracy of ±0.5°C.
The cells were also cycled with 0.5C 1C, 5C and 10C discharge rates.
The relaxation time were reduced from three hours to one hour. The
test procedure started with the cells being charged to 100% SoC and
rested for 3 hours before each discharge event. For analysis purposes
only discharge curves were considered.
Analysis
Quantitative analysis of the results of the tests performed on the cells
are presented here. The results of the variation in discharge capacity
of the average values of the two cells as a percentage from the
reference test defined in the methodology section are shown in Figure
7. The first observation is the range of capacity variation from the
reference for all the different cases in Figure 7 is 1% to 14.2% under-
estimation and 0.3% to 4.7% over-estimation. In general, a trend of
under-estimation of the capacity across the varying C-rates and wait
times for low temperature test is observed except for the combination
of higher C-rates and shorter wait times. Thus for the worst case in
terms of a high C-rate of 10C and reduced relaxation time from 3
hours to 1 hour at a temperature of -10°C, an over-estimation is
observed instead of the continued trend of under-estimation. This is
believed to be due to the cell warming due to increased impedance
during low temperature cycling. For this worse case the thermocouple
temperature at position F4 in Figure 6 for the two cells reaches a
value of 57.2°C on average during the 10C with 1 hour relaxation
time discharge test. For ambient temperature (20°C) and high
temperature tests there is a general trend of over-estimation of the
capacity measurement. The red marker indicates the reference test
described in the methodology section with parameters: 1C discharge
rate, 3 hours relaxation time at a test temperature of 20°C.
From Figure 7 it is clear that low temperature testing results in the
greatest variability in capacity test results. By changing the C-rate
while keeping the relaxation time constant at 3 hours (shown in the
left hand side of Figure 7) the variation in the capacity at 20°C is
0.7% to 1.2% over-estimation. The maximum variation of a 1.2%
over-estimation is observed at the 10C discharge which is 54 minute
saving in test time compared to the reference test.
Figure 7. Average delta (∆) in capacity as a percentage versus various C-rates
and wait times for different temperatures.
For the 1C discharge at 20°C with a 1 hour relaxation time the
capacity measurement is over-estimated by only 1.9% compared to
the reference test with 3 hours relaxation time. This translates to a 2
hour reduction in total test time with a variation in capacity of less
than 2% and demonstrates scope for reduction of test time by
reducing relaxation time. For the test cases where the relaxation time
were reduced to 1 hour, the -10°C tests capacity measurement varies
from a 10.9% under-estimation to a 1% over-estimation.
To better understand this under-estimation trend that changes to an
over-estimation trend with an increase in C-rate at -10°C, the voltage
versus capacity curves for the different C-rates at -10°C is presented
in Figure 8.
-17.0
-12.0
-7.0
-2.0
3.0
8.0
0.5C(1
hour)
1C(1
hour)
5C(1
hour)
10C(1
hour)
0.5C(3
hours)
1C(3
hours)
5C(3
hours)
10C(3
hours)
Average ∆ in capacity from reference(%)
C-rate and relaxation time
-10°C 0°C
20°C 40°C
Reference test

Page 10 of 15
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Figure 8. Voltage versus capacity curves for various C-rates at -10°C.
Real-world testing a high volume of LIBs at low temperature would
not be feasible due to the high amounts of energy needed to condition
cells at low temperatures and cost penalty for specialised equipment
used to test the cells at these temperature extremes. Testing may not
always be performed at ambient temperatures in some geographical
locations due to some extreme environmental temperatures that the
LIB could be exposed to. The purpose of evaluating capacity
measurements at extremes like -10°C was to study the variability of
the capacity test results in order to establish if the need for
environmental temperature control was necessary or not. From Figure
8 it can be seen that the initial voltage of the 0.5C through to 10C
discharge rate drops significantly due to the relation:
       (12)
With  the cell voltage,  the open circuit voltage, the
internal cell impedance, the cell charge/discharge current which
relates to each other as shown in the basic equivalent circuit model
(ECM) shown in Fig 9. This decrease in  is due to the   
component of equation 12 for which an increased C-rate results in
larger current and  will initially be the same at the start of
discharge when the cell was soaked at -10°C. For the 0.5C discharge
rate a gradual reduction in cell voltage is observed. The 10C
discharge curve shows an initial rise in voltage from 2 Ah capacity to
9 Ah capacity due to the warming of the cell. There is also a steeper
drop in voltage at the end of discharge for the 10C curve in Figure 8
compared to curves with lower C-rates. This is due to the fact that the
minimum voltage of the cell at 2V is being reached faster.
Comparing Figure 8 and Figure 10 it can be seen that at -10°C the
increase in C-rate results in a gradual capacity increase compared to
the curves for tests performed at 20°C. The curves in Figure 10 for
tests performed at 20°C shows a very slight increase in capacity for
higher C-rates. This gradual increase in capacity is due to the gradual
degrease in cell impedance which is a direct result of the cells
warming due to increased current flow. The heat generated from the
cell is governed by:

    (13)
Figure 9. Basic ECM for a battery.
With 
 the heat generated by the cell in Watt,  charge/discharge
current and  the internal cell impedance. The slope of the voltage
increase gets significantly steeper for the 10C discharge rate
compared to the 1C discharge curve in Figure 8 due to the square
relation between cell heat and current. For the high temperature test
performed at 40°C the capacity decreases slightly with increasing C-
rate as shown in Figure 11 and a similar drop in initial voltage as C-
rate increases seen in Figure 8 is observed. At the higher temperature
cell warning will not have such a significant effect as seen with cold
temperature cycling, thus the  will be roughly equal for the
various discharge currents presented in Figure 11. The slight capacity
decrease is due to the minimum cell voltage being reached faster with
higher C-rates.
Figure 10. Voltage versus capacity curves for various C-rates at 25°C.
For the 20Ah cells that was used an expected measurement error of
5.81% was calculated by analysing the variability in cell resistance
and OCV from the goods-inward test of the cell batch.
When the best case scenario in terms of test time saved compared to
the reference test time is considered, the optimal parameters are a
10C discharge with a 1 hour relaxation time at 20°C. This will result
in a 172 minute saving in test time with a capacity measurement that
is only 2.9% over-estimated.
1.5
2
2.5
3
3.5
4
0 5 10 15 20
Voltage (V)
Capacity (Ah)
Temperature at -100 C
Cell 2: 0.5C Cell 2: 1C
Cell 2: 5C Cell 2: 10C
1.5
1.7
1.9
2.1
2.3
2.5
2.7
2.9
3.1
3.3
3.5
0 5 10 15 20
Voltage (V)
Capacity (Ah)
Temperature at 200 C
Cell 2: 0.5C Cell 2: 1C
Cell 2: 5C Cell 2: 10C

Page 11 of 15
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Figure 11. Voltage versus capacity curves for various C-rates at 40°C.
The 2.9% is still significantly lower than the expected 5.81% in
measurement error discussed in the previous paragraph and can
therefore still be an acceptable level of accuracy for a characterisation
test for remanufacturing.
Discussion
From the initial discussion the importance of remanufacturing as a
potential best case for EoL for EV LIB is established. Current state of
the art for remanufacturing across various sectors is discussed and
assessed from an EV LiB remanufacturing point of view. The
importance of testing in remanufacturing is highlighted and the
parameters relevant to the LIB SoH that needs to be optimised for
shorter overall test times in identified.
Key variables namely temperature, C-rate and relaxation wait times
have been identified as controlling factors for total test time. By
reducing the total test time through varying temperature, C-rate and
relaxation wait times, the accuracy of the capacity measurements at
different temperatures is affected. The accuracy together with cost
feeds directly into the feasibility of testing associated with the reverse
logistics chain for remanufacturing. Lengthy test times will lead to
costly and unnecessarily long tests to achieve extremely accurate
results that are not fit for purpose.
The results of the experiments presented here show that there is scope
to improve test times by optimising the three main test parameters
that affect test time. The capacity tests performed on two 20Ah pouch
cells showed larger sensitivity to test temperature compared to C-rate
and relaxation wait time sensitivities. The results also show that a test
time reduction of 2 hours can be achieved by reducing relaxation wait
time alone. Further smaller time reductions can be achieved by
increasing the C-rate at which cell discharging is performed. Further
investigation into low temperature testing showed that cell capacity is
heavily affected by cell warming due to increased C-rates and that a
cell voltage increase can occur during discharging.
Further work on this topic needs to be performed in order to
investigate the possibility to reduce the test time even more. The
relaxation time needs to be further reduced and the robustness of test
parameter optimisation for different cell chemistries needs to be
evaluated.
Summary/Conclusions
Remanufacturing is currently one of the most sustainable EoL options
for EV LIBs. Although highly accurate measurements are essential for
research purposes, the test times to achieve such high accuracy are
excessive and not feasible from a remanufacturing point of view. The
research presented in this paper show that for capacity measurements
it is possible to perform the tests at a faster C-rate which will reduce
the time of the total test.
For a more drastic reduction in total test time, the wait time before a
charge and discharge event can be significantly reduced from 3 hours
to one hour without losing significant accuracy. Thus by reducing
wait time, testing time is reduced making it more feasible to test in a
remanufacturing scenario. Total test time reduction with acceptable
accuracy levels of 72.5% is achieved by optimising the test relaxation
wait time, C-rate and temperature. Reduced total test time will also
translate to lower labour cost, which in turn will reduce process cost
and advance a feasible remanufacturing strategy.
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Contact Information
Jakobus Groenewald is with Warwick Manufacturing Group,
University of Warwick, Coventry CV4 7AL, UK, (phone: 024-765-
23794 e-mail: j.groenewald@warwick.ac.uk).
Acknowledgments
The research presented within this paper is supported by Innovate UK
through the ABACUS Collaborative Research Project (project no.
101897) in partnership with Jaguar Land Rover, Potenza Technology
and G+P Batteries. This research is also supported through the
WMG Centre High Value Manufacturing (HVM) Catapult.