The effects of lithium sulfur battery ageing on second-life possibilities and environmental life cycle assessment studies

energies Article The Effects of Lithium Sulfur Battery Ageing on Second-Life Possibilities and Environmental Life Cycle Assessment Studies Deidre Wolff1,* , Lluc Canals Casals 1,2, Gabriela Benveniste 2, Cristina Corchero 1,2 and Lluís Trilla 1 1Catalonia Institute for Energy Research (IREC), Sant Adriàde Besòs 08930, Spain; [email protected] (L.C.C.); ccorcher[email protected] (C.C.); [email protected] (L.T.) 2Universitat Politècnica de Catalunya (UPC), Barcelona 08034, Spain; gaby[email protected] *Correspondence: [email protected]; Tel.: +34-933-562-615 Received: 29 May 2019; Accepted: 24 June 2019; Published: 25 June 2019   Abstract: The development of Li-ion batteries has enabled the re-entry of electric vehicles into the market. As car manufacturers strive to reach higher practical specific energies (550 Wh/kg) than what is achievable for Li-ion batteries, new alternatives for battery chemistry are being considered. Li-Sulfur batteries are of interest due to their ability to achieve the desired practical specific energy. The research presented in this paper focuses on the development of the Li-Sulfur technology for use in electric vehicles. The paper presents the methodology and results for endurance tests conducted on in-house manufactured Li-S cells under various accelerated ageing conditions. The Li-S cells were found to reach 80% state of health after 300–500 cycles. The results of these tests were used as the basis for discussing the second life options for Li-S batteries, as well as environmental Life Cycle Assessment results of a 50 kWh Li-S battery. Keywords: energy storage ageing and degradation; life cycle assessment; second-life energy storage applications; Li-Sulfur batteries 1. Introduction The history of the electric vehicle (EV) is full of back and forth. It was born in the 19th century before the first internal combustion engine vehicle (ICEV), but was soon abandoned. It resurged in the 1890s by the hand of General Motors but was also soon abandoned. It was not until the arrival of lithium ion batteries, with their clearly higher performance in comparison to other energy storage systems, that the EV again entered the market in 2010. This time, though, apart from technical and economic issues, the development and implementation of country and region-specific environmental policies and directives was crucial for market penetration [1]. With the market share of electric vehicles (EVs) increasing and EV adoption being widely debated [ 2 ], research related to EV energy consumption, environmental impact and economic impact has increased on a yearly basis [ 3 ]. As part of this, and due to the increasing interest of adopting Circular Economy principles, Life Cycle Assessment studies have been conducted to quantify the environmental impact of EVs with the goal of reducing the pressure on ecosystems and natural resources [4]. Life Cycle Assessment (LCA) is the current state-of-the-art for quantifying the environmental life cycle impact and is thought to be valuable for assessing the potential impact of moving towards an electrified transportation infrastructure [ 5 ]. LCA is defined as the “compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle” [ 6 ]. LCA studies of EVs have focused on impact categories such as climate change and Energies 2019,12, 2440; doi:10.3390/en12122440 www.mdpi.com/journal/energies Energies 2019,12, 2440 2 of 19 energy demand. This is due to the fact that variation in the electricity grid mix has a large influence on the overall result, and thus decarbonization of the grid mix will lead to further improvements in the environmental impact of the EV [ 7 ]. Along the same line, improvements in driving range and efficiency of the battery will also lead to a lower environmental impact. Therefore, many efforts have focused on the environmental analysis of the use phase of the EV. However, components such as batteries, that generally use scarce and precious materials, also present environmental concerns that need to be addressed, such as resource depletion. An LCA approach is necessary to give a more complete picture of the environmental burdens caused by EVs, from raw material extraction through to final disposal. In order to normalize the results from one LCA study to the next, most studies have assumed a total lifetime driving distance above 100,000 km [ 8 , 9 ], a consumption of between 0.12 [ 10 ] and 0.2 kWh/km [ 11 , 12 ], and a battery lifespan that is equivalent to that of the EV. Other studies have conducted scenario analysis on the driving distance, the consumption, and the battery lifespan (including one or more battery replacements [ 13 ]). In terms of End-of-Life (EoL) of the EV battery, degradation to 80% of the initial battery capacity is considered the appropriate lifespan for mobility purposes, after which the battery should be replaced [ 14 ]. However, this 80% limit has been debated in relation to the real needs of the EV owner [ 15 ], as trips are often well below 100 km [ 16 ] and may still be supported with a battery below the suggested 80% State of Health (SoH). Once the battery reaches its EoL, there is an opportunity to reuse the battery in stationary applications [ 17 ], referred to as the second life of the battery [18]. There are three main strategies to consider regarding second life batteries, each having positive and negative aspects. The first suggests that the best option from an economical perspective is to use the batteries exactly as they are when extracted from the vehicle, without any further manipulation. The battery pack is installed as one unit in a portable container [ 19 , 20 ], or a tertiary building knowing that the battery might not be the most suitable for the stationary application. The second strategy is based on the concept that the battery re-use should concentrate on modules, which are relatively easy to dismantle from the battery pack and will allow for the battery to be sized according to the second life application. In this case, the repurposed battery can use modules from different car manufacturers [ 21 ]. Finally, the third strategy suggests that the dismantling of the EV battery should be at cell level in order to select the cells that have similar degradation. This selection allows perfectly homogeneous batteries to be built [ 22 ]. However, besides the choice of the strategy and stationary application to use, there are still other issues to consider before a positive revenue is generated from the defined business case, such as battery ownership and battery collection, among others [23,24]. Battery performance is another aspect being considered for increased deployment of EVs. Not all Li-ion batteries are equal, differing in the chemical composition of the anode, cathode and doping elements to provide various performance characteristics, such as higher energy density, higher power density, longer lifespan or improved safety. Currently, nickel manganese cobalt oxide (NMC) batteries are preferred by the automotive sector [ 25 ] due to their relatively high energy density, acceptable lifespan and safety level. Another chemical composition used by Chinese car manufacturers is Iron phosphate (LFP) that has a lower cost and good lifespan but provides lower energy and power densities compared to NMC. Finally, nickel cobalt aluminum oxide batteries (NCA) provide higher energy and power densities than NMC, but have lower lifespans and safety inconveniences [ 26 ]. Due to the different options available for Li-ion batteries, research has been done to analyze the environmental impact of battery manufacturing. Studies have indicated that the preferred NMC batteries perform worse than the other types from an environmental perspective [13,27]. Despite the quite good technical performance of Li-ion batteries that allowed the return of EVs, the cost of the batteries is still too expensive for a massive deployment [ 28 ]. Moreover, car manufacturers aim to reach specific energies of approximately 550 Wh/kg to increase the battery capacity and reduce the overall weight of EVs, and in turn eliminate range anxiety concerns of EV owners. Since Li-ion batteries are thought to have achieved their practical specific energy limit [ 29 ], which ranges between Energies 2019,12, 2440 3 of 19 100 and 250 Wh/kg, new alternatives for battery chemistry are being considered that have higher practical specific energy limits, such as Li-Sulfur (Li-S) [ 30 ], lithium air, and all-solid-state batteries [ 31 ]. From the aforementioned alternatives to Li-ion, the research presented in this study focuses on Li-S technology as part of the work conducted under the framework of the HELIS H2020 project [ 32 ] that aims to develop Li-S batteries for automotive purposes. This paper first presents the analysis of the Li-S battery ageing tests that were conducted on in-house manufactured Li-S cells (achieving around 300–500 cycles at 80% SoH). From these results, the second life options and possibilities are discussed together with the results for an environmental Life Cycle Assessment (LCA) study. The LCA is conducted on a 50 kWh Li-S battery and uses the results from the ageing tests to define the lifespan of the battery. The work presented here is focused on the analysis of the evolution of the capacity related to the SoH and the efficiency of the cells. The study of the internal mechanisms that lead to degradation, material activation and self-discharge will not be addressed in this paper, but will be included in future work. 2. Materials and Methods This section is divided into two subsections. The description of the cell ageing tests and how the results will be treated is presented in the first section. The second section presents the environmental LCA methodology. 2.1. Ageing Tests The ageing tests of the Li-S technology were performed by exposing in-house manufactured coin cells to endurance tests under laboratory conditions in a thermal chamber. Note that these coin cells were part of the second generation of cells resulting from the HELIS project. The cell composition was based on a sulfur-carbon composite cathode and Li-metal anode. The cathode was fabricated using a conventional doctor blade approach, consisting of 80% sulfur-carbon composite, 10% conductive carbon and 10% Polyvinylidene fluoride (PVDF) binder. Electrodes were punched in a disc and dried at 80 ◦ C prior to the manual coin cell assembly. The cells contained 2 mgS/cm 2 /side with a theoretical capacity of 1675 mAh/gS yielding the final capacity in the range of 1 mAh, although some variability was observed due to the manual manufacturing process. An optimized amount of 1M lithium bistrifluoromethanesulfonimidate (LiTFSI) in 1:1 dimethyl glycol (DME) and dioxolane (DOL) electrolyte [ 33 ] was used, resulting in a ratio of about 35 µ L/mgS. It is noted here that this ratio was used in the coin cells for project purposes to ensure cell performance, but was reduced when scaling to larger cell sizes. The testing platform included a Bio-Logic BCS series potentiostat with 24 channels for multiple simultaneous testing, an Angelantoni FM600BT climatic chamber for low temperature testing and a DRY-line VWR oven to regulate high temperatures (Figure 1). At the end of the tests, EC-lab software was used to extract all data for further analysis. Energies 2019, 12, x FOR PEER REVIEW 3 of 20 considered that have higher practical specific energy limits, such as Li-Sulfur (Li-S) [30], lithium air, and all-solid-state batteries [31]. From the aforementioned alternatives to Li-ion, the research presented in this study focuses on Li-S technology as part of the work conducted under the framework of the HELIS H2020 project [32] that aims to develop Li-S batteries for automotive purposes. This paper first presents the analysis of the Li-S battery ageing tests that were conducted on in-house manufactured Li-S cells (achieving around 300–500 cycles at 80% SoH). From these results, the second life options and possibilities are discussed together with the results for an environmental Life Cycle Assessment (LCA) study. The LCA is conducted on a 50 kWh Li-S battery and uses the results from the ageing tests to define the lifespan of the battery. The work presented here is focused on the analysis of the evolution of the capacity related to the SoH and the efficiency of the cells. The study of the internal mechanisms that lead to degradation, material activation and self-discharge will not be addressed in this paper, but will be included in future work. 2. Materials and Methods This section is divided into two subsections. The description of the cell ageing tests and how the results will be treated is presented in the first section. The second section presents the environmental LCA methodology. 2.1. Ageing Tests The ageing tests of the Li-S technology were performed by exposing in-house manufactured coin cells to endurance tests under laboratory conditions in a thermal chamber. Note that these coin cells were part of the second generation of cells resulting from the HELIS project. The cell composition was based on a sulfur-carbon composite cathode and Li-metal anode. The cathode was fabricated using a conventional doctor blade approach, consisting of 80% sulfur-carbon composite, 10% conductive carbon and 10% Polyvinylidene fluoride (PVDF) binder. Electrodes were punched in a disc and dried at 80 °C prior to the manual coin cell assembly. The cells contained 2 mgS/cm2/side with a theoretical capacity of 1675 mAh/gS yielding the final capacity in the range of 1 mAh, although some variability was observed due to the manual manufacturing process. An optimized amount of 1M lithium bistrifluoromethanesulfonimidate (LiTFSI) in 1:1 dimethyl glycol (DME) and dioxolane (DOL) electrolyte [33] was used, resulting in a ratio of about 35 µL/mgS. It is noted here that this ratio was used in the coin cells for project purposes to ensure cell performance, but was reduced when scaling to larger cell sizes. Figure 1. Image of the testing equipment. Figure 1. Image of the testing equipment. Energies 2019,12, 2440 4 of 19 A total of six cells were tested combining different temperatures ( − 10 ◦ C, room temperature and 45 ◦ C) and current (C-rate) conditions (from C/5 to 2C) to determine which (if any) of these factors can be considered the principal ageing factors that accelerate the ageing phenomena that occurs in all types of batteries: •Room Temperature (RT), C-rate: 2C (J26) •Room Temperature (RT), C-rate: C/10 (provided by SAFT Battery Manufacturer) •Temperature −10 ◦C, C-rate: C/2 (J4) •Temperature −10 ◦C, C-rate: C/5 (J1) •Temperature 45 ◦C, C-rate: 2C (J33) •Temperature 45 ◦C, C-rate: C/5 (J32) Note that there was only one cell per test due to the channel limitations of the equipment and the duration of the experiments. Although one cell might not be enough to ensure the absolute validity of results, it was preferred to test different scenarios rather than just a few but with a redundancy in the number of cells following the same profiles. It should also be noted that the second cell, cycled at room temperature (RT) and following a 10 h charge/discharge cycle profile, had the particularity to be the only cell manufactured by SAFT, the battery manufacturer in the HELIS project. All the other cells (J1, J4, J26, J32 and J33) were built in the Catalonia Institute for Energy Research (IREC) facilities following manual processes. Furthermore, at –10 ◦ C, the operative capacity of the cells submitted to relatively high rates was residual (less than 10% of the capacity identified at room temperature), being impossible to retrieve reliable information from these tests, which is the reason that the maximum cycling rate at –10 ◦C was done at C/2 instead of 2C. All the endurance tests at low C-rates followed non-stop symmetric constant current capacity cycles. That is, charges and discharges, which have the same C-rate (no matter if it is a charge or discharge process) occurred consecutively without any pause between cycles and without having a constant voltage period to achieve a full charge. All charges stopped at a maximum voltage of 2.6 V while discharges stopped when the minimum of 1.9 V was reached. Moreover, the capacity fade presented in the results section are directly extracted from these continuous cycling and not from specific “control cycles.” Note that the continuous constant current cycling allows the batteries to age relatively quickly compared to using constant current-constant voltage strategies, but it goes in detriment of reliability, as the resulting data might present higher dispersion. On the other hand, due to the particularities of the charge/discharge voltage profile of Li-S, the effective or functional capacity of a cell might dramatically change depending on the C-rate but independently of the ageing of the cell. Consequently, the instant performance of Li-S should be clearly differentiated. Figure 2(left) shows that the behavior of the discharge of Li-S batteries clearly has three phases, an initial small voltage drop (an abrupt step just after the beginning of a charge or discharge) of about 0.2 V (from 2.6 to 2.4 V), followed by a continuous voltage decrease and, finally, a plateau that has a slight voltage recovery prior to the final descent of voltage until reaching the minimum limit of 1.9 V. This is the common behavior of a Li-S battery as the kinetics of the polysulfides inside the cell are related to voltage [ 34 ]. However, when exposed to higher currents (Figure 2right), the initial voltage drop caused by the internal resistance is much higher (around 0.4 V) forcing the minimum voltage of 1.9 V to be reached during the continuous voltage decrease of the second phase and before entering in the last plateau [ 35 ]. In consequence, the functional capacity of the cell is divided by almost 2, and thus should be considered during the ageing analysis. Energies 2019,12, 2440 5 of 19 Energies 2019, 12, x FOR PEER REVIEW 5 of 20 Figure 2. Charge/discharge voltage profile of a cell cycling at C/5 (left) and at 2C (right). Additionally, as five of the cells were manufactured in-house following a non-industrialized process, their capacity is substantially lower than the cell built by SAFT (Table 1) and they also have quite a large dispersion between themselves. It is worth to remark that all cells were manufactured using the same active materials and electrolyte and contain the same sulfur loading, the differences observed here are due to the manufacturing process (manual and industrial) and the inherent imperfections linked to the manual processing of the components. Table 1. Initial capacity of cells. Cell Number Initial Capacity (mAh) J1 1.97 J4 1.18 J26 0.83 J32 0.92 J33 0.68 SAFT 2.62 Due to the low capacity and large dispersion, the battery degradation was evaluated by analyzing the evolution of SoH through the endurance cycling tests. In this study, the SoH is calculated as the ratio between the capacity at the current cycle discharge divided by the capacity of the first discharge done by the cell (Equation (1)). SoH = Capi/Cap, (1) where Capi is the initial Capacity and Cap is the capacity at the current cycle. Using this process, the degradation of the battery can be easily compared between the different endurance tests to be able to extract the functional effects of temperature and current intensity to the available capacity. Note that for cells having lower capacity, the small dispersion caused by the measurement equipment is amplified when relating it to SoH. To ease the interpretations of the evolution of SoH results and the trends derived from them, one data point from every 100 cycles is presented in the graphics in the results section (to have fewer overlapping data points in the same graph). Note that the presentation of results as SoH versus cycles instead of SoH versus capacity throughput (Ah) is also clearer due to the relatively important data dispersion of the initial capacity of the in-house manufactured cells. In addition, the study also analyzes the degradation of the battery in terms of efficiency, which is related to the internal resistance increase of the cells [36]. To do so, the study considers the ratio between the total capacity (Ah) charged to the cell divided by the capacity discharged from the cell for each cycle (Equation (2)). Eff = Ah Charge/Ah Discharge. (2) To understand the exact evolution of the resistance, pulse tests [37,38], or even more precise methods, such as Electrochemical Impedance Spectroscopy (EIS) [39–41], could have been used. However, as the main scope of the study was to evaluate the functional characteristics of the cells and their relation to the End-of-Life, Second Life applications and LCA, it was decided that the SoH and 1.8 2 2.2 2.4 2.6 2.8 0 5 10 15 20 25 Voltage (V) Time (hours) J32 - C/5 at 45ºC 1.8 2 2.2 2.4 2.6 2.8 0 0.1 0.2 0.3 Voltage (V) J33 - 2C at 45ºC Figure 2. Charge/discharge voltage profile of a cell cycling at C/5 (left) and at 2C (right). Additionally, as five of the cells were manufactured in-house following a non-industrialized process, their capacity is substantially lower than the cell built by SAFT (Table 1) and they also have quite a large dispersion between themselves. It is worth to remark that all cells were manufactured using the same active materials and electrolyte and contain the same sulfur loading, the differences observed here are due to the manufacturing process (manual and industrial) and the inherent imperfections linked to the manual processing of the components. Table 1. Initial capacity of cells. Cell Number Initial Capacity (mAh) J1 1.97 J4 1.18 J26 0.83 J32 0.92 J33 0.68 SAFT 2.62 Due to the low capacity and large dispersion, the battery degradation was evaluated by analyzing the evolution of SoH through the endurance cycling tests. In this study, the SoH is calculated as the ratio between the capacity at the current cycle discharge divided by the capacity of the first discharge done by the cell (Equation (1)). SoH =Capi/Cap, (1) where Capiis the initial Capacity and Cap is the capacity at the current cycle. Using this process, the degradation of the battery can be easily compared between the different endurance tests to be able to extract the functional effects of temperature and current intensity to the available capacity. Note that for cells having lower capacity, the small dispersion caused by the measurement equipment is amplified when relating it to SoH. To ease the interpretations of the evolution of SoH results and the trends derived from them, one data point from every 100 cycles is presented in the graphics in the results section (to have fewer overlapping data points in the same graph). Note that the presentation of results as SoH versus cycles instead of SoH versus capacity throughput (Ah) is also clearer due to the relatively important data dispersion of the initial capacity of the in-house manufactured cells. In addition, the study also analyzes the degradation of the battery in terms of efficiency, which is related to the internal resistance increase of the cells [ 36 ]. To do so, the study considers the ratio between the total capacity (Ah) charged to the cell divided by the capacity discharged from the cell for each cycle (Equation (2)). Eff = Ah Charge/Ah Discharge. (2) To understand the exact evolution of the resistance, pulse tests [ 37 , 38 ], or even more precise methods, such as Electrochemical Impedance Spectroscopy (EIS) [ 39 – 41 ], could have been used. However, as the main scope of the study was to evaluate the functional characteristics of the cells and their relation to the End-of-Life, Second Life applications and LCA, it was decided that the SoH Energies 2019,12, 2440 6 of 19 and efficiency were enough for this analysis and thus these results were not included in this study. The analysis of the internal mechanisms that explains the exact behavior of cells at every instant will be performed in future work. 2.2. LCA Methodology LCA is divided into four stages including, Goal and Scope definition, Life Cycle Inventory (LCI), Life Cycle Impact Assessment (LCIA) and Interpretation. The Goal and Scope definition states the overall goal of the study and defines the system boundary, functional unit, and all other methodological choices required to meet the goal. The functional unit describes the function of the product system being assessed and is the unit for which the data is collected. Often the functional unit is scaled to a more appropriate unit for quantifying the outputs of processes within the system boundary that fulfill the function, referred to as the reference flow [ 6 ]. The LCI is the data collection step, and the LCIA categorizes the LCI data into impact categories defined in the scope, applies the associated characterization model and quantifies the overall environmental impact for each category assessed. The interpretation stage checks that the LCI and LCIA have met the requirements defined in the goal and scope. For this study, an environmental attributional LCA was conducted for the production, use and disposal of a 50 kWh Li-S battery in accordance to ISO 14044 [ 6 ]. The Li-S battery is based on the composition of the Li-S coin cells manufactured in-house and considers the ageing tests as described in Section 2.1. The goal of the study was to quantify the environmental impact of a Li-S battery for use in an electric vehicle from cradle-to-grave, which includes raw material extraction, materials production, battery manufacturing, use and final End-of-Life disposal (Figure 3). It should be noted that the system boundary of the study does not include transportation, the production of the Battery Management System (BMS), or the production of the electric vehicle. Energies 2019, 12, x FOR PEER REVIEW 6 of 20 efficiency were enough for this analysis and thus these results were not included in this study. The analysis of the internal mechanisms that explains the exact behavior of cells at every instant will be performed in future work. 2.2. LCA Methodology LCA is divided into four stages including, Goal and Scope definition, Life Cycle Inventory (LCI), Life Cycle Impact Assessment (LCIA) and Interpretation. The Goal and Scope definition states the overall goal of the study and defines the system boundary, functional unit, and all other methodological choices required to meet the goal. The functional unit describes the function of the product system being assessed and is the unit for which the data is collected. Often the functional unit is scaled to a more appropriate unit for quantifying the outputs of processes within the system boundary that fulfill the function, referred to as the reference flow [6]. The LCI is the data collection step, and the LCIA categorizes the LCI data into impact categories defined in the scope, applies the associated characterization model and quantifies the overall environmental impact for each category assessed. The interpretation stage checks that the LCI and LCIA have met the requirements defined in the goal and scope. For this study, an environmental attributional LCA was conducted for the production, use and disposal of a 50 kWh Li-S battery in accordance to ISO 14044 [6]. The Li-S battery is based on the composition of the Li-S coin cells manufactured in-house and considers the ageing tests as described in Section 2.1. The goal of the study was to quantify the environmental impact of a Li-S battery for use in an electric vehicle from cradle-to-grave, which includes raw material extraction, materials production, battery manufacturing, use and final End-of-Life disposal (Figure 3). It should be noted that the system boundary of the study does not include transportation, the production of the Battery Management System (BMS), or the production of the electric vehicle. Production Anode Production Cathode Production Electrolyte Production Cell Container Production Modular and Pack Packaging Production Cooling System Production Separator Production Battery Assembly Battery Use in EV Battery Disposal Raw Material Extraction System Boundary ElectricVehicle Production ElectricVehicle End-of-life Energy Emissions Waste Energy Emissions Waste Energy Emissions Waste Energy Emissions Waste Energy Emissions Waste BMS Production Transport Figure 3. System boundary for the Life Cycle Assessment (LCA) of the 50 kWh Li-Sulfur (Li-S) Battery. The functional unit of the LCA is defined as 1 km of driving based on an average of 0.17 kWh/km for EVs [ 42 ] and an 85% efficiency [ 43 ] that takes into account both the charge/discharge efficiency confirmed in the results section as well as the efficiency of the charger. The reference flow that is commonly applied in LCA studies of EVs is 150,000 km, particularly for comparisons between EVs Energies 2019,12, 2440 7 of 19 with Li-ion batteries to ICEVs [ 44 ]. Historically, LCA studies conducted on Li-S batteries assumed that the Li-S chemistry would be able to achieve the 150,000 km, however, the degradation curves from laboratory performance tests on Li-S batteries were not included in this assumption. Therefore, another goal of the study was to use the ageing data to determine the total kilometers reached during the lifespan of the battery. In order to include the actual performance of the Li-S battery in the LCA, an alternative reference flow was thus defined as total km for one Li-S battery. The total km was quantified using ageing test data from laboratory tests on Li-S coin cells to calculate the SoH of the battery per cycle. It should be noted that calendar ageing tests were also conducted on the coin cells, however, these results were not considered in the ageing tests for this study as further investigation is required to determine the relationship, if any, between cycle and calendar ageing for Li-S cells. The end-of-life of the battery was defined as 60% SoH for several reasons further discussed in the results section regarding the ageing test performance. The LCA was modeled using GaBi Professional software, a tool designed for LCA studies assessing a variety of impact categories. Both GaBi 8 Professional and EcoInvent 3.5 datasets were used in the study. The electricity mix shown in Figure 4. was used for this study and corresponds to the EU-28 grid mix. Energies 2019, 12, x FOR PEER REVIEW 7 of 20 Figure 3. System boundary for the Life Cycle Assessment (LCA) of the 50 kWh Li-Sulfur (Li-S) Battery. The functional unit of the LCA is defined as 1 km of driving based on an average of 0.17 kWh/km for EVs [42] and an 85% efficiency [43] that takes into account both the charge/discharge efficiency confirmed in the results section as well as the efficiency of the charger. The reference flow that is commonly applied in LCA studies of EVs is 150,000 km, particularly for comparisons between EVs with Li-ion batteries to ICEVs [44]. Historically, LCA studies conducted on Li-S batteries assumed that the Li-S chemistry would be able to achieve the 150,000 km, however, the degradation curves from laboratory performance tests on Li-S batteries were not included in this assumption. Therefore, another goal of the study was to use the ageing data to determine the total kilometers reached during the lifespan of the battery. In order to include the actual performance of the Li-S battery in the LCA, an alternative reference flow was thus defined as total km for one Li-S battery. The total km was quantified using ageing test data from laboratory tests on Li-S coin cells to calculate the SoH of the battery per cycle. It should be noted that calendar ageing tests were also conducted on the coin cells, however, these results were not considered in the ageing tests for this study as further investigation is required to determine the relationship, if any, between cycle and calendar ageing for Li-S cells. The end-of-life of the battery was defined as 60% SoH for several reasons further discussed in the results section regarding the ageing test performance. The LCA was modeled using GaBi Professional software, a tool designed for LCA studies assessing a variety of impact categories. Both GaBi 8 Professional and EcoInvent 3.5 datasets were used in the study. The electricity mix shown in Figure 4. was used for this study and corresponds to the EU-28 grid mix. Figure 4. Electricity grid mix used in the LCA (EU-28 mix). Source: Adapted from GaBi Professional Database. A key limitation of this study includes the scaling up from the composition of a coin cell to a battery. However, including laboratory data from Li-S ageing tests in an LCA case study of Li-S batteries is a step forward for the environmental assessment of this technology. 2.2.1. Li-S Battery Manufacturing Inventory Data The mass of the active material (electrolyte, anode and cathode) in the Li-S coin cells was scaled to the mass of active material required for a 50 kWh Li-S battery based on the gravimetric energy density (GED) and the ratio of total mass to active mass. The GED and active mass were calculated as given in Equations (3) and (4), respectively. As indicated previously, the electrolyte ratio used in the coin cells is 35 µL/mgS for project purposes to ensure proper cell performance. However, since this amount of electrolyte is not optimal and it is assumed that larger cells can reach at least 6 µL/mgS, if not lower, 11.5 µL of electrolyte was estimated as the amount per coin cell for the LCA. It is worth Nuclear 27% Lignite 10% Hard coal 14% Coal gases 1.0% Natural gas 16% Heavy fuel oil 1.9% Biomass 2.8% Biogas 2.1% Waste 1.4% Hydro 12% Wind 9% Photovoltaic 3.2% Figure 4. Electricity grid mix used in the LCA (EU-28 mix). Source: Adapted from GaBi Professional Database. A key limitation of this study includes the scaling up from the composition of a coin cell to a battery. However, including laboratory data from Li-S ageing tests in an LCA case study of Li-S batteries is a step forward for the environmental assessment of this technology. 2.2.1. Li-S Battery Manufacturing Inventory Data The mass of the active material (electrolyte, anode and cathode) in the Li-S coin cells was scaled to the mass of active material required for a 50 kWh Li-S battery based on the gravimetric energy density (GED) and the ratio of total mass to active mass. The GED and active mass were calculated as given in Equations (3) and (4), respectively. As indicated previously, the electrolyte ratio used in the coin cells is 35 µ L/mgS for project purposes to ensure proper cell performance. However, since this amount of electrolyte is not optimal and it is assumed that larger cells can reach at least 6 µ L/mgS, if not lower, 11.5 µ L of electrolyte was estimated as the amount per coin cell for the LCA. It is worth to remark that the electrolyte ratio assumed is closer to the actual for EV-size batteries and provides a more realistic approach for LCA studies. This is further confirmed in [ 45 ], where a ratio of 10 µ L/mgS is recommended when scaling up from coin cells. Similarly, the quantity of lithium anode in the coin cell is in excess, therefore, the diameter of the Lithium ribbon was assumed to be the same diameter as the cathode. For the active material in the cathode, a 1:1 ratio of carbon to sulfur was used. Table 2 Energies 2019,12, 2440 8 of 19 gives the specifications of the coin cells used in scaling up to the 50 kWh battery. The mass of each active material in the battery was calculated using Equations (5) and (6). GED =CCC MAM ×VCC (3) MAM =MElCC +MACC +MCCC , (4) Scaling Factor =1x106 MAM ×EB GED , (5) MXB=MXCC ×Scaling Factor 1000 , (6) where CCC is the capacity (mAh) of the coin cell, VCC is the voltage of the coin cell, MAM is the mass (g) of the active material in the coin cell, MElCC , MACC and MCCC are the masses (g) of electrolyte, anode and cathode in the coin cell, EB is the energy (kWh) of the battery, and GED is the gravitational energy density (Wh/kg). MXB (kg) and MXCC (g) are the masses in kilograms and grams for X (electrolyte, anode or cathode) in the battery (B) and coin cell (CC), respectively. Table 2. Inventory data to calculate Scaling Factor. Specification Quantity Unit Anode (MACC )0.0064 g Cathode (MCCC )0.0078 g Electrolyte (MElCC )0.015 g Mass active material (MAM)0.026 g Mass coin cell (TMCC)3.59 g Capacity (CCC)3.3 mAh Voltage (VCC)2.3 V Capacity Density ( CCC MAM )128.4 Ah/kg Gravimetric Energy Density (GED) 295.4 Wh/kg Energy Li-S Battery (EB)50 kWh The mass of the other battery components, including the cell container, separator, module and pack packaging, and cooling system were taken from a previous LCA study conducted on Li-S batteries [ 43 ], which used the BatPac software for sizing Li-ion batteries and adapted it to a Li-S system. Similarly, data estimated in [ 43 ] for industry manufacturing of Li-S batteries was used for the energy consumption. Table 3gives the quantities used for the 50 kWh Li-S battery. Table 3. Bill of materials for the 50 kWh Li-S battery. Li-S Battery Composition Quantity Unit Data Source Cathode (MCB)51.4 kg Equation (6) Anode (MAB)42.0 kg Equation (6) Electrolyte (MElB)75.9 kg Equation (6) Separator 6.9 kg [43] Cell container 19.6 kg [43] Module packaging 22.6 kg [43] Cooling system 27 kg [43] Pack packaging 41.8 kg [43] Assembly Energy consumption 112,016 MJ [43] 1average value was used. Energies 2019,12, 2440 9 of 19 2.2.2. Li-S Battery Use and End-of-Life Inventory Data The EU-28 grid mix was used for the use phase. Tests for the ageing of coin cells as described in Section 2.1 were used to compute the total amount of kilometers and, thus, extract the energy used during the use phase. To do so, the linear relationship between SoH and number of cycles from the results of the ageing tests served to obtain Equation (7), which was then used to quantify the total use phase energy requirement for each scenario. Three scenarios were defined, being a minimum, average and maximum number of cycles achievable by the battery to reach 60% SoH according to the ageing results for the various cells tested. It should be noted that these scenarios were defined from the cells that cycled for more than 800 cycles during the ageing tests. ET=EB n X i=1 (mn +b)=EB mn(n+1) 2+nb!, (7) where ET is total accumulated energy (kWh), EB is the energy of the battery (kWh), m and b are the slope and intercept of the fit linear curve for SoH versus cycle number, respectively, and n is the cycle number. Data for the recycling of Li-S batteries was provided by ACCUREC (project partner) who developed a recycling process for Li-S cells that is in compliance with EU-directive 66/2006. This directive sets a minimum recycling efficiency requirement for batteries of 50% of the mass of the battery. 2.2.3. Impact Categories Assessed The LCA data was aggregated into impact categories and summed to give a total result. The impact categories assessed include resource depletion, acidification, eutrophication, climate change, photochemical ozone formation and energy demand. The characterization model and characterization factors used are defined in Table 4. Table 4. Description of impact categories assessed. Impact Category Characterization Factor Unit Model Description Resource Depletion Abiotic Depletion Potential (ADP elements) kg Sb-eq. CML 2001Jan 2016 The depletion of reserves due to the unsustainable extraction of non-renewable minerals Acidification Acidification Potential (AP) kg SO2-eq. CML 2001Jan 2016 The emission of substances that lead to the change in soil acidity and ecosystem damage Eutrophication Eutrophication Potential (EP) kg PO4−3-eq. CML 2001Jan 2016 The release of nutrients that lead to growth of algae and cyanobacteria and a relative loss in species diversity Climate Change Global Warming Potential (GWP) kg CO2-eq. CML 2001Jan 2016 The emission of greenhouse gases that lead to increased radiative forcing and raise in mean global temperature Photochemical Ozone Formation Photochem. Ozone Creation Potential (POCP) kg C2H4-eq. CML 2001Jan 2016 The emission of substances that undergo photochemical reactions to form ozone at ground level which leads to human health impacts and ecosystem damage Energy Demand Primary energy demand (ren. and non-ren. resources, PED) MJ PED, gross calorific value The consumption of both renewable and non-renewable primary energy sources measured prior to processing Energies 2019,12, 2440 16 of 19 After analyzing the results from the endurance ageing tests, it seems that Li-S batteries do not follow the same patterns of Li-ion batteries. It was found that the temperature and C-rate seem to produce no acceleration of ageing, and that there is no dramatic change in the ageing tendency as is seen in Li-ion batteries when they reach the “ageing knee” or “sudden death.” For Li-S batteries, the cells either continue to cycle or crash instantaneously, meaning they can no longer absorb or deliver energy. Furthermore, the efficiency of Li-S batteries decreases constantly, that is, an exponential loss of efficiency is not visible which is in contrast to the behavior of Li-ion batteries. From an ageing perspective, these factors make Li-S batteries preferable to Li-ion batteries, as their behavior appears “more predictable” and they seem to be unaltered due to external factors related to the application environment. In terms of battery second life applications, this may not be foreseen for Li-S batteries. Future batteries are expected to have larger capacities of up to the 50 kWh as described in this study, and thus the End-of-Life of the battery in an EV (first life) could be lower than the targeted 80% SoH (60% or even lower) and still be capable of satisfying all the driving needs up until the car is recycled. Therefore, it is not only the inherent complexities of their normal operability that limits the second life applications, but also both the low SoH at the beginning of the second life corresponding to a lower capacity and the fact that the batteries will be quite old (possibly 15 years old) at the end of the first life. In this duration, newer and more interesting batteries will likely be on the market at reasonable prices. In terms of the LCA case study conducted for a 50 kWh Li-S battery, it was found that both the production and use stages of the life cycle contribute to the overall environmental impact for all impact categories assessed, except for resource depletion (ADP) where the production stage is the key contributor. For the use phase, three scenarios for the cycle life of the battery were defined based on the ageing test results conducted on Li-S cells. It was found here that the 50 kWh Li-S battery has the potential to achieve the 150,000km usually defined in LCA case studies of EVs. For the production stage of the life cycle, the active material in the battery (anode, cathode and electrolyte) contributes greater than 70% to all impact categories assessed except for resource depletion (ADP) where the electronics in the module packaging is the largest contributor. It is noted here that the data quality for scaling the active material from a coin cell to that in a 50 kWh battery will be improved and should be updated in the LCA as better data from larger batteries is available, along with the efficiencies and driving ranges defined for the Li-S technology. However, in this study it was shown that with improvements in the Li-S technology, the environmental impact per kilometer will improve as the number of cycles the battery achieves during its first life improves. Furthermore, the use of laboratory data for the ageing of Li-S cells in an LCA study is a step forward for the assessment of the environmental impact of this technology. Author Contributions: Conceptualization, C.C.; Data curation, L.C.C.; Formal analysis, D.W. and L.C.C.; Funding acquisition, C.C.; Investigation, D.W., L.C.C., G.B. and L.T.; Methodology, D.W. and G.B.; Project administration, G.B., C.C .and L.T.; Resources, G.B. and L.T.; Software, G.B.; Supervision, C.C.; Validation, C.C.; Visualization, D.W. and L.C.C.; Writing—original draft, D.W. and L.C.C.; Writing—review and editing, D.W., L.C.C., G.B., C.C. and L.T. Funding: This research received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 666221 (www.helis-project.eu). C. Corchero’s work is supported by the grant IJCI-2015-26650 (MICINN). Acknowledgments: We would like to acknowledge ACCUREC for their contribution of data for the recycling process of the Li-S cells. Conflicts of Interest: The authors declare no conflict of interest. References 1. Sierzchula, W.; Bakker, S.; Maat, K.; Van Wee, B. 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