Automotive Battery Research Articles

Effect of anode binders on low-temperature performance of automotive lithium-ion batteries

The effect of styrene-butadiene rubber (SBR)/sodium salt of carboxymethyl cellulose (CMC) and poly(vinylidene fluoride) (PVdF) binders in the anodes on low-temperature performance and cyclability of automotive Li-ion batteries is investigated in 2.0 Ah cylindrical 18650 cells, composed of LiNi0.5Co0.2Mn0.3O2 as cathodes and graphite as anodes. The physical and electrochemical properties of SBR/CMC and PVdF anodes are characterized to compare their low-temperature performance. It is found that the adhesion strength of the SBR/CMC anode is slightly higher than that of the PVdF anode. On the other hand, because of its lower glass transition temperature (Tg), higher ionic conductivity and better absorption of the electrolyte, the PVdF anode results in higher electrical and ionic conductivity than observed in the SBR/CMC anode at low temperatures. These properties of the PVdF anode contribute to smaller impedance and faster Li-ion diffusion. Thus, the PVdF anode exhibits better discharge behavior and cycle performance at low temperatures than the SBR/CMC anode.

Size distribution and elemental composition of vent particles from abused prismatic Ni-rich automotive lithium-ion batteries

Abstract The lithium-ion battery (LIB) jet is often accompanied by particulate matter (PM) (e.g. spark) during vent and combustion caused by thermal runaway. These hot PM could ignite the combustible vent gases, and the settleable matter may promote water and soil pollution. The aim of this study is to reveal the statistical size distribution and elemental composition of the settleable PM released by LIBs after thermal runaway. A fully charged commercial 50 Ah Li(Ni0.6Mn0.2Co0.2)O2 cell was triggered by heating in a sealed chamber. These PM were divided into 4 samples using sieves. The sizes were analyzed and the elements were detected. The results show that these PM account for 11.20% of the cell mass. Nearly 45% of particles by mass were found to have a size less than 0.85 mm, with the median size being approximately 198 um. The main elements are carbon, nickel, cobalt, etc. The content of metallic elements is approximately 40%. The emissions also contain potentially toxic elements, including aluminum, lithium, fluorine, etc. The element species in different samples are similar, but their contents differ. The size distribution provides a basis for the design of the particle filter pore, and elemental composition reveals the pollution of LIB emissions.

Performance Analysis of PI and SMC Controlled Zeta Converter

This paper presents the design and analysis of DC-DC Zeta converter operating in the continuous conduction mode to regulate the output voltage of the converter for automotive battery recharge applications. The state space analysis of the converter is derived to obtain the transfer function of the converter. The presented DC-DC converter exhibits the non-linearity due to the presence of energy storage elements and degrades the performance of the converter. Therefore, this paper proposes a non-linear cascaded Proportional -Integral Sliding Mode Controller (PI-SMC) to improve the performance of the converter. PI-SMC Controller contains PI Controller in the outer loop for voltage regulation and an inner fast acting SMC Controller for current shaping. The PI controller is tuned by Root locus and Routh Hurwitz criterion and the steady state performance parameters are obtained for the PI-SMC Controlled Zeta converter. MATLAB/SIMULINK results are presented for Set point tracking of the controller. The results shows that the steady state performance indices such as Integral Absolute Error (IAE) and Integral Time Absolute Error (ITE) are significantly enhanced for the converter using the proposed cascaded control scheme compared to the conventional PI controller.

Learning human-understandable models for the health assessment of Li-ion batteries via Multi-Objective Genetic Programming

The health of automotive Li-ion batteries depends on different side reactions on the electrodes that may degrade the cells, thereby reducing their useable capacity and sometimes producing catastrophic failures with serious economic and safety implications. In this paper, a method of detection and prognosis of battery deterioration is proposed in which an intelligent soft sensor is able to synthesize human-understandable health indicators from sequences of voltages, currents and temperatures streamed via on-vehicle sensors. This soft sensor is based on a dynamic model optimizing three different criteria obtained by means of multi-objective grammatical evolution. Different survival selection strategies suitable for this problem are discussed and compared.

10-Min Fast Charging of Automotive Li-Ion Batteries at an Elevated Temperature

Fast charging technology is widely recognized as a critical factor in bolstering consumer appeal of battery electric vehicles (BEVs). The U.S. Department of Energy (DOE) has set a goal of developing extreme fast charging (XFC) battery technology that can recharge a 200-mile BEV in 10 minutes. A key barrier to XFC of automotive Li-ion batteries is the issue of lithium plating, which drastically deteriorates battery life and even induces hazardous consequences. Fundamentally, lithium plating is affected by the rate capability of ion transport in the electrolyte, intercalation reaction at graphite surface, and solid-state diffusion in graphite particles. Research in the literature, accordingly, has been focusing on improving electrolyte transport properties, enhancing charge transfer kinetics, or utilizing smaller particles. Li-ion battery is well known for its trade-off nature. Improving one property without sacrificing others is always challenging. An alternative approach to suppressing lithium plating is to elevate charge temperature. Indeed, an increase in temperature can boost the rate capability of the above three processes simultaneously. However, an elevated temperature, on the other hand, accelerates the solid-electrolyte-interphase (SEI) growth. Owing to the interplay between lithium plating and SEI growth, it is universally believed that Li-ion batteries have an optimal life at room temperature. [1] In 2018, our group presented a numerical study revealing that the optimal temperature of a Li-ion battery, in contrary to the conventional wisdom, actually increases with an increase of charge rate and/or energy density.[2] Enlightened by this finding, we proposed a heated-charge method [2, 3] to charge a Li-ion cell at an elevated temperature of 40-60oC to enable XFC without Li plating. Very recently, Tesla has applied this concept in its V3 superchargers. Using an ‘On-route Battery Warmup’ strategy, Tesla vehicles are designed to arrive at a fast charging station at a temperature of ~40oC, demonstrating the commercial viability of charging a BEV at an elevated temperature. Nevertheless, a potential issue of Tesla’s on-route warmup strategy is the slow heating speed, making a battery stay at a high temperature for a long period of time and hence incurring excessive SEI-induced degradation. Currently, we are developing an XFC battery based on the heated-charge method. With a novel structure, our battery has >100x faster heating than conventional external heating methods, thereby limiting the duration of heating to a matter of seconds. More profoundly, we will present in this talk that our battery, having an energy density of 210 Wh/kg, could sustain 2,000 cycles of 10-min (6C) charge to 80% state of charge with only 7% capacity loss.

Three dimensional numerical validation and investigation on air cooling system of Li-ion battery used in hybrid electric vehicles

The lithium ion batteries are most commonly used in hybrid electric vehicles for obtaining high energy density among the condemnatory issues that have been in automotive industry. As the thermal management system is very prominent in automotive batteries, an effective design consideration is to be carefully opted for cooling the battery. Especially, a forced cooling is followed as an empirical choice rather than natural cooling in the automotive industry. In this paper, a three dimensional battery pack with multiple cells and cooling passages is modelled and validated to maximize the durability and battery performance. An enumerated design of air-cooled system is validated from the literature and then numerically investigated the overall distribution of the temperature with different cases by changing the positions of the inlets and outlets of the battery to satisfy the thermal specification requirements of the battery. Since, a distinctive battery system is used in hybrid electric vehicle which contains multiple cells in parallel, cooling efficiency is accomplished by a uniform diffusion of air flow in the coolant passages which dissipates the heat evolved from the individual lithium-ion battery cell. The above four cases are compared and demonstrated that the efficient cooling performance is attained with the one inlet and one outlet which are placed at the opposite sides of the battery. This is acquired because, the faster the air flow rate, the more the system cools due to the high temperature dissipation.

Recycling and Re-Use of Lithium-Ion Batteries (ReLiB)

Newcastle University is part of the Recycling and Re-use of Lithium-ion Batteries (ReLiB) project that aims to facilitate the creation of a UK re-use/recycling industry to recycle > 90% of automotive batteries. It is in order to make better use of global resources, increased decarbonisation and ultimately dedicate to mitigate the climate change issues. The project tackles the most demanding technical challenges in sensing, gateway testing, robotic sorting, re-use and recycling of batteries coming from EVs. The project is extremely wide-ranging covering everything from lifecycle, technical and economic assessment and legal liability issues, to tackling the most demanding technical challenges in sensing, gateway testing, robotic sorting, re-use and recycling of automotive batteries. The £9M ReLiB project is led by Birmingham University and includes a total of eight universities and 14 industrial partners. ReLiB was funded by the UK’s flagship Faraday Institution that supports research, training, and analysis in the electrochemical energy storage, science and technology. At Newcastle University, the team is assessing risk, identifying safe management methods and developing response protocols for handling used batteries. Abuse of Lithium ion batteries by overcharging or short circuit can lead to fire or even explosion, and one of the tasks of the Newcastle University team in close collaboration with researchers from the Extreme Robotics Lab of the University of Birmingham is to trains robots to disassemble the battery packs. This will be achieved by the use of various 3-D analyses and imaging techniques with the aim of removing . Ultimately, that will remove any risk to human health when disassembling very high voltage and high energy automotive batteries. The Newcastle team is investigating energy management applications and developing non-destructive testing techniques (NDT) to predict and certify the second lifetime. A set of NDTs (e.g. Electrochemical Impedance Spectroscopy and thermal imaging) are being employed to assess the state of health (SOH) of batteries in order to make a decision regarding whether a module or cell should be re-used or recycled, in a so-called ‘gateway’ test for re-use or materials recovery. Results so obtained will be compared to analytical data from teardown at the University of Birmingham and material analyses at the University of Leicester and with the aim of identifying potentially dangerous ageing mechanisms such as lithium plating. Using gateway sensing, the NU team will develop new assessments for low carbon transport strategies and characterise the performance of second-life battery packs operating in power and energy ancillary service markets. The suitability of second life batteries for various applications will be explored in terms of technical performance, life-cycle costing and the challenges of integration into existing and future infrastructure systems. This understanding will feed directly into economic models for reuse. In addition, new business models and regulatory frameworks will be investigated in conjunction with the complete, full-cycle value chain. A detailed understanding of second life battery pack lifetime will hence be developed and demonstrated. Other academic partners are investigating various processes, approaches and techniques with the aim of achieving the maximum value for the components and minimising the cost of processing. These include: physical processing, upgrading of battery components, pyrometallurgical recovery of metals and novel biological recovery routes. The re-use/recycling processes will be subjected to Life Cycle Assessment in order to evaluate their environmental impact and pick the one with the smallest footprint. Such a comprehensive approach is designed to give the collaborating recycling companies a competitive edge in the growing market. The increasing application of LiBs in electric vehicles and high energy storage systems has led the Newcastle team to realise there is an urgent need for the education of the public, businesses, government organisations and the emergency services in the safe handling of LiBs and hazards associated with these devices when involved in fires. To this end, the ReLiB team is advising a range of organisations including the Fire and Rescue Service, the Department for Transport and the CBI, and is actively seeking to disseminate specialist help and advice to a broader range of stakeholders. The team is due to carry out fire safety tests on LiBs in collaboration with the Tyne and Wear Fire Service in order to aid them in refining their firefighting procedures for fires involving an electric vehicle. Figure 1

On Ionic and Covalent Cross-Linking of Alginic Acid Derived Binders for High Capacity Silicon Anodes

The anode market for automotive Li-ion batteries is still governed by carbonaceous materials with a market share of 96%.[1] The graphite electrodes used today can only deliver a moderate capacity of 300-350 mAh/g, and improvements are highly sought. Silicon, often in the form of a silicon/carbon composite, is a promising alternative material with its high theoretical capacity of about 3600 mAh/g. As an alloy former this capacity is accompanied with a huge volume change of over 300%, deeming PVDF unsuitable as binder as it cannot withstand the volume changes upon cycling. A variety of technical and biopolymers were shown to drastically increase the cyclability of silicon based anodes. Prominent examples are s poly (acrylic acid) (PAA), carboxymethyl cellulose (CMC) and alginic acid (algin) derivatives. Algin, often purified as water soluble Na alginate, is a polysaccharide found in the cell walls of brown algae. It consists of the two epimers D-mannuronic acid (M) and L-guluronic acid (G), which's content and distribution have a strong impact on the 3D structure and properties. Superior cycling of Na alginate bound Si anodes was first described by Kovalenko et al..[2] The incorporation of divalent ions such as calcium, strontium, barium or transition metals causes strong chelation of the ions resulting in a hydrogel. Several studies have described that this ionic cross-linking has a profound effect on the cyclability of Si based anodes. [3],[4],[5],[6] Divalent ions are usually chelated by two adjacent G units on two polymer chains forming a so called egg-box and high degrees of saturation cause gelling, which obstructs processing. Since chelation including G units only is much stronger than the interaction with M groups, the M to G ratio should have a strong effect on the stability of the network. Covalent cross-linking should have an even stronger effect on the stability of the binder network as it is constructed of chemical bonds rather than ionic interactions. This study concerns the effect of different saturation degree of calcium and barium cross-linking on alginates with different M to G ratio as binder for Si based anodes. Furthermore, we discuss routes to form a covalently cross-linked algin derived network that is grafted to the Si surface. [1] Schmuch R., Wagner R., Hoerpel G., Placke T., Winter M., Performance and cost of materials for lithium-based rechargeable automotive batteries, Nature Energy, 3 (2018), 267-278. [2] Kovalenko, I., et al., A Major Constituent of Brown Algae for Use in High-Capacity Li-Ion Batteries. Science, 2011. 334(6052): p. 75-79. [3] Wua Z-Y., Deng L., Li J-T., et al. Multiple hydrogel alginate binders for Si anodes of lithium-ion battery. Electrochimica Acta, 245 (2017), 371–378. [4] Gu Y., Yang S., Zhu G., et al. The effects of cross-linking cations on the electrochemical behavior of silicon anodes with alginate binder, Electrochimica Acta, 269 (2018), 405-414. [5] Zhang L., Zhang L., Peng L. C., et al. A coordinatively cross-linked polymeric network as a functional binder for high-performance silicon submicro-particle anodes in lithium-ion batteries, J. Mater. Chem. A,2 (2014), 19036–19045 [6] Yoon J., Oh D. X., Jo C. et al., Improvement of desolvation and resilience of alginate binders for Si-based anodes in a lithium ion battery by calcium-mediated cross-linking, PCCP, 16 (2014), 25628-25635. Figure 1

Rapid State-of-Health (SoH) Determination and Second-Life Grading of Aged Automotive Battery Modules Via Electrochemical Impedance Spectroscopy (EIS)

The number of electric vehicle (EV) batteries reaching end-of-service is set to increase from thousands to tens of thousands per annum by 2025. These end-of-service batteries typically retain significant capacity and power delivery capability, and their re-use in so-called ‘second-life’ applications has been proposed as a means to extend the battery value chain, offset a portion of their up-front cost and minimise waste by deferring recycling. Accurate grading of used battery assets is essential in order to assign them an appropriate valuation in the second-life market. These grading activities account for the majority of the cost incurred in repurposing batteries at present, due largely to the time required for testing, which typically employs DC techniques taking up to several hours to perform a capacity measurement. Rapid grading methodologies are required to reduce processing time and achieve the levels of throughput required to handle increasing quantities of end-of-service batteries. Electrochemical Impedance Spectroscopy (EIS) is a promising technique for determination of SoH, offering results in minutes instead of hours. However, EIS measurements are affected by extraneous factors such as temperature, state-of-charge and the experimental setup, and do not provide a direct measurement of capacity. The deployment of EIS for battery grading therefore requires a careful approach in order to eliminate noise factors and ensure robustness, and necessitates modelling in order to interpret output in terms of capacity. Here, we present a methodology for rapid grading of aged automotive Li-ion batteries using EIS, and demonstrate its application to battery modules from the 1st generation Nissan Leaf. An empirical model has been developed, which is capable of inferring the residual capacity of an aged module from measurements of its EIS spectrum, open-circuit voltage and temperature made within 3 minutes using a Solartron impedance analyser. The model was derived from data gathered using a design-of-experiments approach, employing numerous used battery modules covering a range of states-of-health. EIS measurements were recorded under different conditions in order to understand and correct for the influence of key noise factors. We demonstrate that the SoH of a vehicle battery can be determined in minutes using EIS, instead of hours using traditional DC techniques, with no loss of accuracy, repeatability or reproducibility. The process is now being implemented for grading of battery modules at Nissan’s Sunderland plant in the UK, and significantly reduces the time required for complete characterisation of a used battery pack. Reduction of characterisation time in this way affords a corresponding reduction in repurposing costs, thus improving the viability of battery re-use as part of the circular economy. This work was undertaken within the UK Energy Storage Laboratory project funded by the UK Government Department for Business, Energy and Industrial Strategy (BEIS) and in conjunction with Nissan Motor Manufacturing UK and Element Energy.

Modeling Volume Change of Large Format Pouch Cells Due to Intercalation

Most current production electric vehicles (EVs) contain cells within a battery pack or module in order to maintain electrical conductivity, prevent fatigue due to vibrations, and provide efficient cooling. Modules may contain cooling fins, thermistors, foam separators, and repeating frame elements to hold the cells. As the cells expand and contract during cycling, the stresses generated can cause the materials in the battery module to deform and crack. This fatigue can result in a loss of electrical or thermal contact and therefore, decreased range, reduced battery life or loss of function, or a loss of heat transfer fluid which could result in electrical shorts. Therefore, it is critical to properly design modules and packs to properly account for the volume change inherent in these pouch cells. Currently, empirical mechanical data is used to predict the thickness changes of cells with varying electrode porosities, chemistries, and thicknesses. The ability to relate electrode expansion to electrochemical operation and accurately predict cell volume change would save significant time in experimental efforts as well as material costs. Previously, our group developed a coupled electrochemical and mechanical model that accurately predicts the split between electrode porosity and dimensional changes [1-3]. Here, we employ our model along with lithiation-based particle expansion data for graphite [4], lithium nickel-manganese-cobalt oxide (NMC) [5], and lithium manganese oxide (LMO) [5], to predict the thickness change of a large-format pouch cell used in automotive battery packs. Then, we measured the thickness of the cell as the cell was discharged from .99 to .01 state-of-charge. Figure 1 shows the predicted anode and cathode strain compared to the measured cell displacement divided by the sum of the anode and cathode thicknesses. This method allows battery pack designers to appropriately account for new cell types using electrochemical performance and individual particle-level expansion parameters as inputs. Design considerations, as well as cell level volume changes will be discussed.

The Effect of Volume Change on the Accessible Capacities of Porous Silicon-Graphite Composite Anodes

Lithium-silicon chemistries show promise to increase battery capacity; however, silicon expands significantly during lithium intercalation, leading to inaccessible capacities as well as cell or pack failure due to pressure generation. Silicon-graphite (Si/C) composite anodes are used to increase the anode capacity while maintaining a tolerable degree of active material volume expansion. Recently, Dash and Pannala modeled anodes with increasing Si/C ratios and explored the tradeoff between increasing gravimetric capacity and the increasing active material volume expansion upon Li intercalation [1]. Their conclusion highlights that while the gravimetric capacity increases, there is ultimately a “threshold value” where the volumetric capacity will begin to decrease to account for the significant silicon volume expansion. Here, we built upon this concept to account for electrochemical and mechanical design limitations applicable to battery pack design for electric vehicles (EVs). We propose that increasing the Si/C ratio does not directly lead to an increase in the accessible capacity, because excessive volume expansion can lead to unacceptable cell pressure or electrode porosity. In order predict the accessible capacity as a function of Si/C ratio, we integrated mechanical behavior for each individual cell component (e.g., composite anode, cathode, and foam packing) into our previous battery model [2-4]. This model can predict the split between changes in electrode porosity and dimensions by coupling component mechanical behavior to the volume change governed by electrochemical phenomena. We employed our model to simulate a full charge of a pouch-style battery within a flexible packing, similar to those seen in current automotive battery packs. The simulations were used to determine the accessible capacity as a function of Si/C ratios, using mechanical design limitations relevant to EV batteries, pressure and porosity. Pressure limitations represent the pressures that may cause capacity loss, the strain of a frame element containing the cells, or the cracking of a cooling components. Minimum porosity limitations represent the porosity requirements of different cell types (e.g., a power cell must have a high porosity while an energy cell can tolerate lower porosities). We can then predict the ideal Si/C ratio to optimize capacity while meeting the associated design requirements. Figure 1 shows the accessible gravimetric and volumetric capacities based on pressure limitations for a cell within flexible packing. The solid and dotted lines represent the accessible capacities for 250 kPa and 500 kPa design limitations, respectively. In addition to determining accessible capacities, our model could be used to observe individual component mechanical behavior as a function of SOC. Figure 2 shows each individual cell component displacement as well as the overall cell displacement as a function of SOC. Predicting the overall cell swelling is helpful when trying to select internal cell materials as well as the foam packing material. This information can also be useful in aiding EV battery designers to appropriately design the overall battery pack while accounting for the cell’s displacement and pressure generation inside the pack.

Mathematical Modeling of Lithium Sulfur Batteries

Present day automotive battery packs typically consist of a large number of LIBs (few hundreds to thousands) to meet the required power and capacity needs of an EV. The high cost and limited mileage of present LIB-powered cars are due to the intrinsic limited capacities of the Li-ion insertion cathodes, which are nearing their practical limits and even a two-fold increase in energy density of current LIB cells is insufficient for the long-term demands of transport and electricity storage. Hence, for a wide deployment of EVs and maximizing electrification of the road transportation system, drastic improvements in today’s battery pack performance is needed. Among new generation of lithium batteries, high theoretical energy density (~600 Wh/Kg) that may be 4-5 times higher compared to that of Li-ion batteries, good low-temperature performance, and abundance of inexpensive nontoxic raw material, make the lithium sulfur batteries (LSB) a promising candidate for major energy applications. However, there are several major issues facing rechargeable LSBs that impede their practical applications. In other words, challenges such as fast capacity loss, limited cycle life, high self-discharge rates, over-heating, and volume change of the cathode have hindered mass commercialization of these cells and limit their current application to UAVs and defense applications where the lightness and high energy is more important than life cycle. Although a wide range of experimental researches have investigated novel strategies, material and designs for the cells, the mathematical and theoretical studies are scarce. Theoretical modeling plays crucial role in the exploration of the phenomena happening in the LiS cells. A mathematical model is presented to provides a better understanding of the complex multistep electrochemical reactions, side reactions, multiscale and multi component transport phenomena, phase change phenomena and precipitation reaction, and porosity and volume change of the cathode.

(Invited) Requirements and Challenges for Next Generation Automotive Batteries

E-mobility is at a tipping point with increasingly optimistic forecasts for the future market share of electric vehicles. However, for electrified vehicles to achieve mass-market penetration, new powertrains must achieve a reasonable balance between driving range, power, charge rate, safety and cost. Optimization of the battery pack down to the cell, electrode and material levels offers the potential for many performance improvements, yet each change necessitates significant re-tailoring of a cell. Such multivariable optimization requires high-throughput evaluation methods as well as a deep understanding of electrochemical, chemical and mechanical fundamentals. To apply demanding automotive requirements to new battery technologies, BMW Group works with academic, national lab, and industry partners to understand the impacts of each cell design decision. Some innovations (e.g. advanced electrolytes) are challenging to discover but simple to implement, while others (e.g. high-Si content anodes, all-solid-state electrolytes) require significant R&D inputs in both discovery and scalability. This presentation will outline the opportunities and limitations of various cell and material concepts from a car manufacturer’s point of view. Key challenges will be addressed with examples from BMW research projects.

Effect of Fast-Charging on Ageing of Energy-Optimized Automotive LiNi1/3Mn1/3Co1/3O2/Graphite Prismatic Lithium-Ion Cells

It is desirable to be able to charge automotive batteries at a fast rate, especially for heavy duty commercial vehicles. In this study [1] the effect of fast charging (1C-4C) on ageing was studied on an energy-optimized 25 Ah prismatic NMC(III)/graphite lithium-ion cell cycled at 35°C and 20-80% SOC. Detailed post-mortemanalysis was carried out using scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and electrochemical impedance spectroscopy (EIS). The results show that the effect of charging rate is more complex than earlier described. Even though ageing is more rapid at 3 and 4C charging, no clear trends in degradation with charging rate are observed. Instead, different mechanisms are dominating at the different charging rates. Accelerated lithium plating was observed after cycling at 3C-charging, while extensive gas evolution was the cause to the fast cell impedance rise and capacity fade of the cells cycled at 4C. Graphite exfoliation and accelerated lithium inventory loss point to the graphite electrode as the source of the gas evolution. SEM show cathode particle cracking independent of the charging rate used for the cycling. XPS and EIS generally indicate thicker surface film and larger impedance, respectively, towards the edge of the cells. The results implicate that the ageing rates are too high to be feasible for a battery electric inner-city bus using this type of cell being charged at 3C. However, even though ageing rates for 2C and below are acceptable, it is concluded too slow from the point of view of practical charging time. Fig. Capacity fade vs. number of equivalent full cycles (inset: capacity fade vs. cycling time). Fast-charging effects on ageing for energy-optimized automotive LiNi1/3Mn1/3Co1/3O2/ graphite prismatic lithium-ion cells. Abdilbari Shifa Mussa, Anti Liivat, Fernanda Marzano, Matilda Klett, Bertrand Philippe, Carl Tengstedt, Göran Lindbergh, Kristina Edström, Rakel Wreland Lindström, Pontus Svens, Journal of Power Sources 422, 2019, 175-184.

Predicting the Thickness Change of a Large Format Pouch Cell during Operation

Most current production electric vehicles (EVs) contain cells within a battery pack or module in order to maintain electrical conductivity, prevent fatigue due to vibrations, and provide efficient cooling. Modules may contain cooling fins, thermistors, foam separators, and repeating frame elements to hold the cells. As the cells expand and contract during cycling, the stresses generated can cause the materials in the battery module to deform and crack. This fatigue can result in a loss of electrical or thermal contact and therefore, decreased range, reduced battery life or loss of function, or a loss of heat transfer fluid which could result in electrical shorts. Therefore, it is critical to properly design modules and packs to properly account for the volume change inherent in these pouch cells. Currently, empirical mechanical data is used to predict the thickness changes of cells with varying electrode porosities, chemistries, and thicknesses. The ability to relate electrode expansion to electrochemical operation and accurately predict cell volume change would save significant time in experimental efforts as well as material costs. Previously, our group developed a coupled electrochemical and mechanical model that accurately predicts the split between electrode porosity and dimensional changes [1-3]. Here, we employ our model along with lithiation-based particle expansion data for graphite [4], lithium nickel-manganese-cobalt oxide (NMC) [5], and lithium manganese oxide (LMO) [5], to predict the thickness change of a large-format pouch cell used in automotive battery packs. Then, we measured the thickness of the cell as the cell was discharged from .99 to .01 state-of-charge. Figure 1 shows the predicted anode and cathode strain compared to the measured cell displacement divided by the sum of the anode and cathode thicknesses. This method allows battery pack designers to appropriately account for new cell types using electrochemical performance and individual particle-level expansion parameters as inputs. Design considerations, as well as cell level volume changes will be discussed.

Globally regional life cycle analysis of automotive lithium-ion nickel manganese cobalt batteries

Electric vehicles based on lithium-ion batteries (LIB) have seen rapid growth over the past decade as they are viewed as a cleaner alternative to conventional fossil-fuel burning vehicles, especially for local pollutant (nitrogen oxides [NOx], sulfur oxides [SOx], and particulate matter with diameters less than 2.5 and 10 μm [PM2.5 and PM10]) and CO2 emissions. However, LIBs are known to have their own energy and environmental challenges. This study focuses on LIBs made of lithium nickel manganese cobalt oxide (NMC), since they currently dominate the United States (US) and global automotive markets and will continue to do so into the foreseeable future. The effects of globalized production of NMC, especially LiNi1/3Mn1/3Co1/3O2 (NMC111), are examined, considering the potential regional variability at several important stages of production. This study explores regional effects of alumina reduction and nickel refining, along with the production of NMC cathode, battery cells, and battery management systems. Of primary concern is how production of these battery materials and components in different parts of the world may impact the battery’s life cycle pollutant emissions and total energy and water consumption. Since energy sources for heat and electricity generation are subject to great regional variation, we anticipated significant variability in the energy and emissions associated with LIB production. We configured Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model as the basis for this study with key input data from several world regions. In particular, the study examined LIB production in the US, China, Japan, South Korea, and Europe, with details of supply chains and the electrical grid in these regions. Results indicate that 27-kWh automotive NMC111 LIBs produced via a European-dominant supply chain generate 65 kg CO2e/kWh, while those produced via a Chinese-dominant supply chain generate 100 kg CO2e/kWh. Further, there are significant regional differences for local pollutants associated with LIB, especially SOx emissions related to nickel production. We find that no single regional supply chain outperforms all others in every evaluation metric, but the data indicate that supply chains powered by renewable electricity provide the greatest emission reduction potential.

Microbial Pb(II)-precipitation: the influence of oxygen on Pb(II)-removal from aqueous environment and the resulting precipitate identity

The study aimed to quantify the lead(II) bio-precipitation effectiveness, and the produced precipitate identities, of industrial consortia under aerobic and anaerobic batch conditions. The consortia were obtained from an automotive battery recycling plant and an operational lead mine in South Africa. The experiments were performed in the complex growth medium Luria–Bertani broth containing 80 ppm lead(II). The precipitation and corresponding removal of lead(II) were successfully achieved for both aerobic (yellow/brown precipitate) and anaerobic (dark grey/black precipitate) conditions. The removal of lead(II) followed similar trends for both aeration conditions, with the majority of lead(II) removed within the initial 48 h, followed by a marked decline in removal rate for the remainder of the experiments. The final lead(II) removal ranged between 78.11 ± 4.02% and 88.76 ± 3.98% recorded after 144 h. The precipitates were analysed using XPS which indicated the presence of exclusively PbO and elemental lead in the aerobic precipitates, while PbO, PbS, and elemental lead were present in the anaerobic precipitates. The results indicated an oxidation–reduction mechanism with lead(II) as an electron acceptor in both aerobic and anaerobic conditions, while a sulphide-liberation catabolism of sulphur-containing amino acids was evident exclusively in the anaerobic runs. This study provides the first report of bacterial bio-reduction in aqueous lead(II) to elemental lead through a dissimilatory lead reduction mechanism. It further provides support for the application of bioremediation for the removal and recovery of lead from industrial waste streams through the application of bacterial biocatalysts for direct elemental lead recovery.

Remaining useful life prediction based on degradation signals using monotonic B-splines with infinite support

Degradation modeling traditionally relies on monitoring degradation signals to model the underlying degradation process. In this context, failure is typically defined as the point where the degradation signal reaches a pre-specified threshold level. Many models assume that degradation signals are completely observed beyond the failure threshold, whereas the issue of truncated degradation signals still remains a challenge. Moreover, based on the physics of a degradation process, the degradation signal should be inherently monotonic. However, it is almost inevitable that most of the sensor-based degradation signals are subject to noise, which can lead to misleading prediction results. In this article, a non-parametric approach to modeling and prognosis of degradation signals using B-splines in a mixed effects setting is proposed. In order to deal with the issue of truncated historical degradation signals, our approach is based on augmenting B-spline basis functions with functions of infinite support. Moreover, to model the degradation signal more accurately and robustly in a noisy setting, necessary and sufficient conditions to ensure monotonic evolution of the modeled signals are derived. Appropriate procedures for online updating of random coefficients of mixed effects model considering derived monotonicity constraints based on degradation data collected from an in-service unit are also presented. The performance of the proposed framework is investigated and benchmarked through analysis based on numerical studies and a case study using real-world data from automotive lead-acid batteries.

Comparing Operando XRD and Dems to Investigate Metal-Substituted LiNiO2

LiNiO₂ (LNO) has been introduced as cathode active material for Li‐ion batteries in 1990 [1]. After years of intensive research, it emerged that several instability issues plague the material, so that it was abandoned in favor of isostructural metal‐substituted compounds called NCA (for lithium nickel cobalt aluminum oxide) and NCM (lithium nickel cobalt manganese oxide). These sacrifice a certain amount of specific energy in exchange for stability, durability and safety [2]. With few exceptions, NCA and NCM are nowadays the industrial standard when it comes to automotive applications. However, the continuous push towards electric cars with longer driving range is synonym, for these compounds, with increasing the nickel content (which is already beyond 80%), eventually leading back again to LiNiO₂. For this reason, we synthesized a series of LiNiO2 samples, where Ni is substituted by low amounts of other elements (< 5%). We implement a characterization strategy based on operando XRD, differential electrochemical mass spectrometry (DEMS) and ex situ TEM, enabling us to track, in real time upon battery charge and discharge (i.e., as Li is extracted/inserted from/into LNO, respectively), the evolution of the material´s crystal structure, the transformation of its surface and the evolution of gaseous products. We place particular emphasis on the behavior of LNO at high state of charge (> 4.1 V), where the transition between the hexagonal phases H2 and H3, whose unit cell volume is very different, induces significant mechanical strain in the material [3]. The H2 and H3 phases are also thermodynamically metastable [4] and decompose towards off-stoichiometric Li1-zNi1+zO2, with release of O2[5], a reaction we can observe by DEMS and TEM. With this combined strategy, we aim at understanding which element, if any, can sufficiently stabilize LNO in the charged state. Bibliography Dahn, J.R., U. Vonsacken, and C.A. Michal, Structure and Electrochemistry of Li1+-yNiO2 and a New Li2NiO2 Phase with the Ni(OH)2 Structure. Solid State Ionics, 1990. 44(1-2): p. 87-97. Myung, S.-T., et al., Nickel-Rich Layered Cathode Materials for Automotive Lithium-Ion Batteries: Achievements and Perspectives. ACS Energy Letters, 2017. 2(1): p. 196-223. Yoon, C.S., et al., Structural Stability of LiNiO2 Cycled above 4.2 V. ACS Energy Letters, 2017. 2(5): p. 1150-1155. Das, H., et al., First-Principles Simulation of the (Li–Ni–Vacancy)O Phase Diagram and Its Relevance for the Surface Phases in Ni-Rich Li-Ion Cathode Materials. Chemistry of Materials, 2017. 29(18): p. 7840-7851. Bianchini, M., et al., There and back again - The journey of LiNiO2 as cathode active material. Angew Chem Int Ed Engl, 2018: p. 10.1002/anie.201812472.

Improving Aging Prediction for Electric Vehicle Operation with Combined Electrical, Thermal and Aging Model for Lithium-Ion Battery Packs Using Quantitative Cell Data

Electric vehicles (EV) in the power grid are not necessarily an additional burden, but can also act grid relieving. This is possible by storing energy from renewable sources and shaving the volatility of generation. For EV battery owners it is important to predict the aging effects resulting from secondary battery use. For a future energy system, it is therefore important to address the topic of EV battery aging for the group of stakeholders: EV owners, EV manufacturers, energy providers and grid operators. A physico-chemically motivated, impedance-based lithium-ion battery model has recently been presented in [6] and is available as open source [5]. Additionally, the authors present a new set of quantitative measurement data for parameterization of a battery pack of Daimler’s Smart electric drive. A battery pack was disassembled to gather all information from inside the battery pack. The cells have been aged as part of an extensive aging testing. Therefore, the simulation setup enables in-situ and operando analysis of cell behavior and helps understanding aging effects in electric vehicle operation. For model parameterization, the research contributions for electrical modeling based on electrical impedance spectroscopy from [1], as well as studies on aging behavior of lithium-ion cells with graphite anode from [2] and [3] are considered and used to adapt the method presented in [4]. The model is parameterized with electrical, thermal and aging parameters for an automotive battery pack that consists of 93 high-energy lithium-ion pouch cells with NMC cathode and graphite anode with a capacity of 50 Ah. A 3D-geometrical representation of the battery pack topology including cooling allows a detailed assessment of the simulated cell temperatures. It therefore helps to generate a better understanding of the incremental battery aging effects that are caused by vehicle-to-grid (V2G) operation. Controlled charging and discharging of EVs could help the grid in terms of stability and avoid additional cost for grid expansion. At the same time, V2G services could generate additional revenues to the EV battery owners from service payment. Nevertheless, calculation of EV battery aging is one major purpose for EV battery owners before they agree to the active use of their EV battery by third parties. Sources: [1] Dissertation H. Witzenhausen, https://doi.org/10.18154/RWTH-2017-03437[2] Dissertation A. Warnecke, https://doi.org/10.18154/RWTH-2017-09646[3] Dissertation M. Lewerenz https://doi.org/10.18154/RWTH-2018-228663[4] Schmalstieg et al., https://doi.org/10.1016/j.jpowsour.2014.02.012[6] Dissertation F. Hust, “Physico-Chemically Motivated Parameterization and Modelling of Real-Time Capable Lithium-Ion Battery Models - a Case Study on the Tesla Model S Battery”, January 2019 [5] www.openbat.de