Lithium-ion (Li-ion) batteries are amongst the most commonly used types in Electric (EVs) and Hybrid Electric (HEVs) Vehicles due to their high energy and power densities, as well as long lifetime. A battery is one of the most important components of an EV and hence it needs to be monitored and controlled accurately. The safety, and reliability of battery packs must then, be ensured by accurate management, control, and monitoring functions by using a Battery Management System (BMS). A BMS is also responsible for accurate real-time estimation of the State of Charge (SoC), State of Health (SoH) and State of Power (SoP) of the battery. The battery SoC provides information on the amount of energy left in the battery. The SoH determines the remaining capacity and health of a pack, and the SoP represents the maximum available power. These critical battery states cannot be directly measured. Therefore, they have to be inferred from measurable parameters such as the current delivered by the battery as well as its terminal voltage. Consequently, in order to offer accurate monitoring of SoC, SoH and SoP, advanced numerical estimation methods need to be deployed. In the estimation process, the states and parameters of a system are extracted from measurements. The objective is to reduce the estimation errors in the presence of uncertainties and noise under different operating conditions. This thesis uses and provides different enhancements to a robust estimation strategy referred to as the Smooth Variable Structure Filter (SVSF) for condition monitoring of batteries. The SVSF is a predictor-corrector method based on sliding mode control that enhances the robustness in the presence of noise and uncertainties. The methods are proposed to provide accurate estimates of the battery states of operation and can be implemented in real-time in BMS. To improve the performance of battery condition monitoring, a measurement-based SoC estimation method called coulomb counting is paired with model-based state estimation strategy. Important considerations in parameter and state estimation are model formulation and observability. In this research, a new model formulation that treats coulomb counting as an added measurement is proposed. It is shown that this formulation enhanced information extraction, leading to a more accurate state estimation, as well as an increase in the number of parameters and variables that can be estimated while maintaining observability. This model formulation is used for characterizing the battery in a range of operating conditions. In turn, the models are integral to a proposed adaptive filter that is a combination of the Interacting Multiple Model (IMM) concept and the SVSF. It is shown that this combined strategy is an efficient estimation approach that can effectively deal with battery aging. The proposed method provides accurate estimation for various SoH of a battery. Further to battery aging adaptation, measurement errors such as sensor noise, drift, and bias that affect estimation performance, are considered. To improve the accuracy of battery state estimation, a noise covariance adaptation scheme is developed for the SVSF method. This strategy further improves the robustness of the SVSF in the presence of unknown physical disturbances, noise, and initial conditions. The proposed estimation strategies are also considered for their implementation on battery packs. An important consideration in pack level battery management is cell-to-cell variations that impact battery safety. This study considers online battery parametrization to update the pack’s model over time and to detect cell-to-cell variability in parallel-connected battery cells configurations. Experimental data are used to validate and test the efficacy of the proposed methods in this thesis. / Thesis / Doctor of Philosophy (PhD) / To address the critical issue of climate change, it is necessary to replace fossil-fuel vehicles with battery-powered electric vehicles. Despite the benefits of electric vehicles, their popularity is still limited by the range anxiety and the cost determined by the battery pack. The range of an electric vehicle is determined by the amount of charge in its battery pack. This is comparable to the amount of gasoline in a gasoline vehicle’s tank. In consideration of the need for methods to address range anxiety, it is necessary to develop advanced algorithms for continuous monitoring and control of a battery pack to maximize its performance. However, the amount of charge and health of a battery pack cannot be measured directly and must be inferred from measurable variables including current, voltage and temperature. This research presents several algorithms for detecting the range and health of a battery pack under a variety of operating conditions. With a more accurate algorithm, a battery pack can be monitored closely, resulting in lower long-term costs. Adaptive methods for determining a battery’s state of charge and health in uncertain and noisy conditions have been developed to provide an accurate measure of available charge and capacity. Methods are then extended to improve the determination of state of charge and health for a battery module.

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京都大学 / 新制・課程博士 / 博士(工学) / 甲第24107号 / 工博第5029号 / 新制||工||1785(附属図書館) / 京都大学大学院工学研究科物質エネルギー化学専攻 / (主査)教授 安部 武志, 教授 作花 哲夫, 教授 阿部 竜 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

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To reach the Swedish goal of reaching a completely fossil-free electricity sector by the year 2040, there is a need for an increased rate of installed renewable electricity sources. Companies have the opportunity to work towards this goal by investing in solar power technologies, which results in a lowered electricity bill, and an additional revenue when electricity is sold to the grid. As a result, the investment usually pays back within a reasonable timeframe. GEHAB is a company located that is located in Alvesta, Sweden, and they are interested in investing in rooftop solar power. This thesis investigates the potential and effects of such an investment at the company through energy simulations. This is done through four different scenarios, which aim at finding the largest possible installation, the most cost-optimal installation, according to the Levelized Cost Of Energy (LCOE), the impact of an added battery installation and finding the current issues with becoming a net-zero consumer of electricity. Finally, a sensitivity analysis was made to investigate how different factors impacted the LCOE. The results showed that the most cost-optimal size for the company to invest in was a 215 kWp installation, which is smaller than the maximum possible size of 335 kWp that can be installed on the rooftop. Such an installation would have an LCOE of -366 SEK/MWh when the avoided costs are included. The discounted payback time of that investment was 11.3 years. The involvement of batteries showed that they would lead to a higher LCOE and for the largest possible solar installation size, including a battery, means that it would not pay back within the lifetime of the PVs. Finally, the net-zero electricity consumption scenario found that currently, the largest issue to reach this scenario is that there is a regulation that limits solar installations to 500 kWp to avoid an energy tax.

Due to climate change, the energy system needs to change from traditional fossil fuels to be dominated by renewable energy sources. Not only the energy system, but the increasing number of vehicles and emissions from the transport sector are a problem for climate change and that need to be solved. Both can be solved with batteries, to handle climate change issue. The lithium-ion batteries (LIBs) have a high energy density which is important due to the less needed materials for the batteries. LIBs can be used in a battery energy storage system (BESS) to store the excess energy for later usage, and as an electric vehicle (EV) battery. For these high energy density batteries, there comes drawbacks such as safety issues by deviating temperatures which have effects on the capacity, lifetime, performance, and in worst case a thermal runaway can occur which may lead to fire and explosions. These temperature issues can be solved with a battery thermal management system (BTMS), which can manage temperature deviation. Cylindrical battery cells with the dimension 18650 with the cell chemistry Lithium-Nickel-Cobalt-Aluminum-Oxide (NCA) will be investigated with different discharge rates, how the heat generation increases, and how it can be handled by cooling systems. A battery pack will be built up in computational fluid dynamics (CFD) software called Ansys Fluent, to be simulated and see how the influence of cooling methods affect the energy density of the 18650 batteries. Air-cooling and liquid-cooling with fan as air-cooling and plate cooling as liquid cooling will be used in this work. 20 cells were investigated with air and liquid cooling, with two different cases with air-cooling. 100 cells with just liquid cooling during 0,5C was investigated on how the number of cells impacted on the energy density. It was seen that the different discharge rates (C-rate) had an impact on the amount of cooling, with air cooling being not as good as liquid cooling for cooling the battery pack and more flow was needed. The energy density in relation to weight showed that 20 cells with less spacing using air-cooling had the best energy density at 196,68 Wh/kg. It was also seen that the number of cells had an impact on the energy density in relation to volume. With the best energy density with 100 cells using liquid cooling at 279,96 Wh/L.

With the current shift towards renewable energy sources, the demand for batteries is expected to follow an exponential increase in the future, and lithium-ion batteries will be the bulk of it. In order to reduce carbon dioxide emissions from battery production and to secure future availability of critical metals, more batteries will need to be recycled. To incentivize this, the European Union will impose regulations on recycling efficiencies as well as recycled content in produced batteries. The purpose of this study was twofold. Firstly, it was to construct a model in Microsoft Excel which could follow the flow of materials from recycling through production and keep track of an inventory which could be allocated to customers as needed. Moreover, the model had to be able to calculate values such as recycled content in produced battery cells and take into account losses from production etc. Secondly, this thesis aimed to use the model to determine how many old cells would have to be recycled in order to produce a modern cell with a certain percentage of recycled content, as well as to determine which recycled active cathode metals there might be surpluses and shortages of. This was done as a case study at the company Northvolt AB, by gathering data from literature, interviews, and site visits. The model was then built iteratively, based on a material flow analysis approach. Finally, the model was used in a methodical manner to test the conversion rates and to determine how big the shortages and surpluses of materials would be. This thesis argues that there is no truly relevant literature on building a material flow and allocation model such as the one required here. However, using the method described above, it was possible nonetheless to construct the novel model. The model consists of several sheets with distinct functions and is scalable while also adaptable to other companies and industries. Among other things, it keeps track of inventory levels with a scalable time axle and helps the user set values to reach target recycled weight percentages. The model can also be used to perform the analyses required for the second half of the purpose of this thesis. The key outcome from that, was that recycling old batteries and producing new ones is far from a 1:1 process and that higher requirements on recycling efficiencies could greatly improve that. Moreover, the active cathode metals which would require the largest amounts of batteries to be recycled in order to produce new cells with recycled content at certain levels, were identified as bottlenecks. When using the required recycling efficiencies from the European Union in 2025 and 2030, the bottleneck metals were lithium and nickel if the new batteries were to contain 100 % recycled active cathode metals. However, if the recycled content should be in line with European Union regulations, the bottlenecks would be cobalt and nickel instead. This could shift the demand for virgin active cathode metals in favor of cobalt and nickel. / Med dagens skifte till förnybara energikällor förväntas efterfrågan på batterier följa en exponentiell ökning i framtiden, och litiumjonbatterier kommer stå för merparten av den. För att minska koldioxidutsläppen från batteriproduktion och för att säkra framtida tillgång till kritiska material kommer fler batterier behöva återvinnas. För att ge incitament till detta, kommer Europeiska unionen införa regleringar på återvinningseffektiviteter och återvunnet innehåll i nya batterier. Syftet med denna studie var tvåfaldigt. Det första syftet var att bygga en modell i Microsoft Excel som kunde följa materialflöden från återvinning genom produktion och hålla kolla på ett lager som kunde allokeras till kunder efter behov. Dessutom behövde modellen kunna räkna ut värden såsom återvunnet innehåll i producerade battericeller samt ta hänsyn till förluster i produktion etc. Det andra syftet var att använda modellen till att bestämma hur många gamla celler som skulle behöva återvinnas för att producera en modern cell med vissa nivåer av återvunnet innehåll, såväl som att bestämma vilka återvunna aktiva katodmetaller det kan bli överskott och underskott av. Detta gjordes som en fallstudie på företaget Northvolt AB, genom att samla data från litteratur, intervjuer och studiebesök. Modellen byggdes sedan iterativt, baserat på en materialflödesanalys. Slutligen användes modellen på ett metodiskt sätt för att testa omvandlingseffektiviteter och bestämma hur stora underskotten och överskotten av material skulle bli. Denna avhandling menar att det inte finns någon riktigt relevant litteratur om att bygga en materialflödes- och allokeringsmodell som den som krävdes här. Med metoderna som beskrevs ovan var det dock möjligt att bygga modellen och bryta ny mark på vägen. Modellen består av flera ark med distinkta funktioner och är skalbar samtidigt som den kan anpassas till andra företag och industrier. Den håller bland annat reda på lagernivåer med en skalbar tidsaxel och hjälper användaren bestämma värden som behövs för att nå målen på återvunna viktprocent. Modellen kan också användas för att utföra de analyser som behövs för att uppfylla andra halvan av avhandlingens syfte. Huvudresultatet från det, är att återvinning av gamla batterier och produktion av nya är långt ifrån en 1:1 process och att högre krav på återvinningseffektiviteter skulle förbättra det markant. Vidare identifierades de aktiva katodmetallerna som skulle kräva de största mängderna återvunna batterier för att producera nya celler med vissa nivåer av återvunnet innehåll. De kallades flaskhalsar. Med Europeiska unionens krav på återvinningseffektiviteter för 2025 och 2030, var flaskhalsmetallerna litium och nickel om de nya batterierna skulle innehålla 100 % återvunna aktiva katodmetaller. Om det återvunna innehållet å andra sidan skulle vara i linje med Europeiska unionens regleringar, skulle flaskhalsarna vara kobolt och nickel istället. Detta skulle kunna skifta efterfrågan på nybrutna aktiva katodmetaller till fördel för kobolt och nickel.

Många batteriers användningsområden kräver att batterierna har hög upp- och urladdningshastighet samt låg kostnad. För dessa användningsområden är vattenbaserade laddningsbara batterier (ARB) ett möjligt alternativ i och med att de är svårantändliga, har god jonledningsförmåga, lägre inre resistans, billigare elektrolytlösning och tillverkning och har potentiellt högre upp- och urladdningshastigheter.  Genom att utgå från en cell med LiMn2O4 och V2O5 som katod respektive anod, utvecklades en cell med en spänning på 1 V och prestanda för 2 mol/L LiTSFI i organisk respektive vattenlöslig lösning jämfördes i ett SEI-fritt system. Prestandan kvantifierades med avseende på urladdningskapaciteten vid olika urladdningshastigheter samt fördelningen av de interna överpotentialerna. Vid C/4 behöll den organiska elektrolyten 88,3% av den initiala kapaciteten efter 10 cykler medan den vattenlösliga behöll 98,8%. En gräns på 20 °C påvisades för den organiska elektrolyten och vid försök att gå över denna hastighet svällde pouch cellen upp. Den vattenlösliga elektrolyten, å andra sidan, bevarade 37 mAh/g vid 50 °C.  Skillnaden i potentialfördelning i de två systemen analyserades även genom att använda tunnare elektroder. Den organiska elektrolyten visade då en förbättring av prestandan vid höga hastigheter, med en urladdningskapacitet på 8,8 mAh/g vid 50 °C, jämfört med 30 mAh/g för den vattenlösliga elektrolyten. IR-fallet var 7 gånger högre för den organiska elektrolyten. Eventuell skillnad i laddningsöverföring och por-resistans kunde inte analyseras då flera processer ägde rum på samma gång i systemen, vilket gav ett impedansspektrum med en komplex associerad ekvivalent krets. / For several battery applications, high dis-/charge rate and low cost are imperatives. It is for these applications that aqueous rechargeable batteries (ARB) rise as potential candidates given the non-flammability, potentially higher ionic conductivity and dis-/charge rates, lower internal resistances and lower price of the electrolyte solvents and manufacture. By benchmarking a cell with LiMn2O4 and V2O5 as cathode and anode, respectively, a cell with an operating voltage window of 1 V was developed and the performance of 2 mol/L LiTFSI in organic and aqueous solvent compared in a SEI-free system. This performance was quantified in terms of discharge capacity at different rates of discharge and the distribution of internal overpotentials. At C/4, the organic electrolyte held 88.3% of the initial capacity after 10 cycles while the aqueous, 98.8%. A limit of 20 °C for the organic electrolyte was seen, and at the attempt of cycling above this rate, swelling of the pouch cell took place. The aqueous electrolyte, on the other hand, conserved 37 mAh/g at 50 °C. The difference of overpotentials distribution in both systems was also assessed by employing thinner electrodes. The organic electrolyte showed then an improvement on high-rate performance, reaching 50 °C, but with a discharge capacity of 8.8 mAh/g, against 30 mAh/g for the aqueous electrolyte. The IR-drop was 7 times higher for the organic electrolyte. The differentiation between charge-transfer and pore resistance, however, was not possible, because of the presence of several processes taking place at similar time-scales in both systems, yielding an impedance spectra with a complex associated equivalent circuit.