Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-ion batteries are increasingly being considered in EVs due to their high energy density, slow loss of charge when not in use, and for lack of hysteresis effect. Conventionally, the batteries are connected in series to achieve the load voltage requirements. However, for the batteries with intrinsic discrepancies or different initial states, cell balancing is a concern because it is the weakest cell that determines the empty point for the battery and an undercharged series cell will shorten the lifetime of the entire pack. The imbalance potential of the battery behaves as the way of State-of-Charge (SOC) mismatch and it’s also temperature dependent. Therefore, in this thesis, an active cell balancing optimization was proposed and conducted in MATLAB to optimize battery unused capacity and thermal effect simultaneously based on bi-directional balancing system and pre-estimated SOC. The bi-directional balancing system was physically built based on “Fly-back” converter to compare balancing performance in discharging, idle, and plug-in charging mode. Moreover, a battery combined model worked collaboratively with robust state and parameter estimation strategies, namely Extended Kalman Filter (EKF) and Smooth Variable Structure Filter (SVSF) in order to estimate SOC for cell balancing. As a result, the proposed method can effectively optimize SOC mismatch around 2.5%. Meanwhile, more uniform temperature was achieved and the maximum temperature can be reduced about 7 ℃. / Thesis / Master of Applied Science (MASc)

Traditional electric vehicle and stationary battery systems use series-connected battery packs that employ centralized battery management and power processing architecture. Though, these systems meet the basic safety and power requirements with a simple hard- ware structure, the approach results in a battery pack that is energy and power limited by weak cells throughout life and most importantly at end-of-life. The applications of battery systems can benefit significantly from modular, scalable battery systems capable of advanced cell balancing, efficient power processing, and cost gains via reuse beyond first-use application. The design of modular battery systems has unique requirements for the power electronics designer, including architecture, design, modeling and control of power processing converters, and battery balancing methods. This dissertation considers the requirements imposed by electric vehicle and stationary applications and presents design and control of modular battery systems to overcome challenges associated with conventional systems. The modular battery system uses cell or substring-level power converters to combine battery balancing and power processing functionality and opens the door to new opportunities for advanced cell balancing methods. This approach enables balancing control to act on cell-level information, reroute power around weaker cells in a string of cells to optimally deploy the stored energy, and achieve performance gains throughout the life of the battery pack. With this approach, the integrated balancing power converters can achieve system cost and efficiency gains by replacing or eliminating some of the conventional components inside battery systems such as passive balancing circuits and high-voltage, high-power converters. In addition, when coupled with life prognostic based cell balancing control, the modular system can extend the lifetime of a battery pack by up to 40%. The modular architecture design and control concepts developed in this dissertation can be applied to designs of large battery packs and improve battery pack performance, lifetime, size, and cost.

Modeling and Implementation of a Hardware Efficient Low-Voltage-To-Cell Battery Balancing Circuit for Electric Vehicle Range Extension / One disadvantage of electric vehicles is their limited driving range when compared to internal combustion engine vehicles. Battery packs are also a significant cost to electric vehicle manufacturers, and lithium-ion battery cells must remain within controlled voltage limits. Thus, the requirements for the electric system are to be cost effective, perform battery management, and make it as efficient as possible to increase its range. Battery packs are typically constructed from around 100 battery cells in a series connection. During use of an electric vehicle, the battery cells become mismatched due to small differences in capacity. This effect is further amplified as the electric vehicle ages. Diverging cells cause issues during driving, since weak cells can limit the useable capacity of the vehicle. In order to use the whole capacity of the battery pack, and thus the entire range of the electric vehicle, the cells should be balanced. Strong cells should distribute their excess capacity to weaker cells during driving. The thesis presents the design, modeling and implementation of a novel hardware-efficient battery balancing circuit. First, the theory behind battery balancing is presented. Next, existing battery balancing circuits are compared. Finally, the proposed battery balancing circuit is discussed. The design of the proposed topology is examined in detail. Simulations show that the circuit transfers energy between non-adjacent cells throughout the entire pack. Experimental work is performed on two custom printed circuit boards, a 12 cell lithium-ion module, and a 12V lead acid battery. The results confirm the function of the prototype. The effect of the battery balancing circuit on driving range is examined with vehicle modeling simulations. A 2018 Chevrolet Bolt model is produced and capacity differences are given to each cell. The proposed topology balances the cells while driving, extending driving range on UDDS and HWFET drive cycles. / Thesis / Master of Applied Science (MASc) / One disadvantage of electric vehicles is their limited driving range when compared to internal combustion engine vehicles. Thus, there is a requirement to make the electric system as efficient as possible in order to increase its range. A large piece of the electric system includes the battery pack. Battery packs are typically constructed from around 100 battery cells in a series connection. During use of an electric vehicle, the battery cells become mismatched. This effect is also amplified as the electric vehicle ages. In order to use the whole capacity of the battery pack, and thus the entire range of the electric vehicle, the cells should be balanced. The thesis presents the design, modeling and implementation of a novel hardware efficient battery balancing circuit. The effect of the battery balancing circuit on driving range is examined.

Batteries account for 50% of the overall cost of solar home systems (SHS). The battery packs degrade over time and when they reach 70% state of health (SOH), the whole SHS is discarded. In the predominantly rural off-grid context, battery replacements are expensive and impractical. The customers are often dozens of km away from any sales point. Furthermore, recycling schemes are often limited in the developing world, meaning that old batteries are sometimes discarded in unsafe ways. As the market grows, the environmental impact of this will only get larger. Solaris Offgrid, a premier name in the Solar Offgrid industry, is innovating two solutions designed to tackle this issue; a smart multi-battery packmanager and an easy to recycle battery pack design with cell by cell management. The current study is based on a lossless cell balancing design, where in the charge and discharge cycles of each cell in the string are monitored and to efficiently avoid overcharge and over-discharge. Implementing this strategy reduces the degradation of these batteries which extends the battery life of SHS. A sensitivity analysis is performed to analyze the environmental benefit gained by implementing lossless cell balancing. The thesis provides a literature study on the different battery terminologies, types of batteries used in SHS and, various cell-balancing techniques used today. This is followed by the design of a lossless cell balancing technique with minimal losses. / Batterierna står för 50 % av den totala kostnaden för solcellsanläggningar (SHS). Batteripaketen försämras med tiden och när de når 70 % av sitt hälsotillstånd kasseras hela solcellssystemet. På den övervägande landsbygden utanför elnätet är det dyrt och opraktiskt att byta ut batterierna. Kunderna befinner sig ofta tiotals kilometer från varje försäljningsställe. Dessutom är återvinningssystemen ofta begränsade i utvecklingsländerna, vilket innebär att gamla batterier ibland kasseras på ett osäkert sätt. I takt med att marknaden växer kommer miljöeffekterna av detta att bli allt större. Solaris Offgrid, som är ett ledande företag inom industrin för solcellsanläggningar, utvecklar två lösningar för att lösa detta problem: en smart batteripackförvaltare för flera batterier och en lätt återvinningsbar batteripackkonstruktion med cellvis hantering. Den aktuella studien bygger på en “förlustfri” cellbalanseringskonstruktion, där laddnings- och urladdningscyklerna för varje cell i strängen övervakas och effektivt undviker överladdning och överladdning. Genom att tillämpa denna strategi minskas degraderingen av dessa batterier, vilket förlänger batteritiden för SHS. En känslighetsanalys utförs för att analysera den miljöfördel som uppnås genom att införa förlustfri cellbalansering. Avhandlingen innehåller en litteraturstudie om olika batteriterminologier, typer av batterier som används i SHS och olika tekniker för cellbalansering som används idag. Detta följs av utformningen av en teknik för förlustfricellbalansering med minimala förluster.

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The electric vehicle industry is experiencing a boom infunding and public interest, and the formula student movementis following suit; an electric race car is currently being developedby the KTH Formula Student organisation (KTHFS) which is thecause of this work.Consumers desire increased speed and range, and are unwillingto compromise one quality for the other. This necessitates the useof lithium ion cells, which may explode and exhume toxic gasesif over-strained with respect to current, charge or temperature.A robust, reliable and provably safe battery management systemshould therefore be developed. There are numerous methods tofurther increase the mileage to get an edge on competitors, suchas cell balancing and live estimation of the State of Charge(SOC). It is also vital that old and/or deteriorated cells should beidentified and disposed off in due time, and State of health (SOH)estimation provides a means to do this. In this paper a completebattery management system software solution is developed andpresented, utilising methods like simulation and code generationto create a program that runs on a real time operating system(RTOS). Some real world test were conducted and some resultsare simulated. The finished BMS performed well in tests, meets allgoals and meets all timing constraints. The project can thereforebe considered as successful. / Intresset för elbilsindustrin har på sistone‌ vuxit något markant, och formula student-rörelsen har anpassat sig efter dessa trender; en elektriskt bil tillverkas just nu av KTH Formula Student organisationen (KTHFS) vilket ger upphov till detta arbete. Marknaden vill ha snabbare bilar som dessutom har förbättrad räckvidd, men vägrar offra den ena egenskapen för det andra. Lösningen är att använda litiumjonceller. Dessa har dock en säkerhetsrelaterad nackdel; om cellerna utsätts för alldeles för höga eller låga temperaturer, strömmar eller laddningsnivåer kan de explodera och utsöndra giftig gas i luften. Därför är det lämpligt att skapa ett batterimonitoreringssystem vars funktion och säkerhet kvalitativt kan utvärderas och bevisas. Det finns flera metoder för att få förbättrad prestanda ur sin ackumulator (batteriensemble); cellnivåbalansering och laddningsnivåestimering (SOC) implementeras i detta projekt. Föråldrade/utslitna celler bör identifieras och avskrivas i god tid. Celldeklineringsestimering (SOH) är ett sätt att lösa detta problem. I denna rapport presenteras en fullständig implementation av mjukvaran för ett batterimonitoreringssystem, där metoder som kodgenerering och simulering utnyttjas för att skapa ett program som kan köras på ett realtidsoperativsystem (RTOS). Vissa test gjordes i verkligheten och vissa resultat simulerades. Det färdiga batterimonitoreringssystemet presterade väl i test, alla mål samt mötte alla tidskrav. Projektet kan därför anses som lyckat. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

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<p dir="ltr">Batteries have become essential for a wide range of applications in the field of energy storage and electrification, from portable gadgets to electric cars and renewable energy systems. But effectiveness, performance, and lifespan of a battery pack are closely related to each of the individual cells of which it is composed. The phenomenon of cell voltage imbalance, which can result in a variety of problems ranging from decreased capacity and efficiency to safety concerns and premature failure, poses a significant challenge in managing battery systems.</p><p dir="ltr">Therefore, battery cell balancing plays a crucial role in improving the overall performance of battery packs. To guarantee uniform charge and discharge characteristics, balancing is the process of equalizing the charge of individual cells inside a battery pack. Battery cell balancing seeks to prolong the operational life of packs, improve the efficiency of its energy use, and ensure the safety of the overall system.</p><p dir="ltr">The methods used for battery cell balancing encompass a wide range of approaches, from passive methods that release extra energy as heat, to active methods that move energy across cells. The particular battery chemistry, application requirements, and required level of balancing precision are only a few examples of the variables that influence the choice of balancing technique.</p><p dir="ltr">Lithium Iron Phosphate (LiFePO4) rechargeable batteries are widely used by electric utility companies in battery storage applications. Battery cells are combined to form a battery module. Each module is constantly monitored with sensors and controlled by a Battery Management System (BMS). The BMS performs balancing of the cells. Each cell in the battery stack is monitored to maintain a healthy battery state of charge (SoC). The motivation for this work is to develop an active balancing system to replace a passive system currently being performed manually on an existing battery storage system consisting of LiFePO4 cells. An active cell balancer was designed using the LT8584 active cell balancer, which is based on a flyback DC-DC converter design. An LTspice simulation of the design was created for a single cell. It demonstrates critical parameters of the flyback converter cycle time. A PCB board, designed using KiCAD, was implemented. It is anticipated that the proposed design could be used to restore the health of SoC of faulty modules in lieu of removing and replacing them with a new module, resulting in potential cost savings. The proposed design is scalable in that it could be used for <i>n</i> number of cells in a battery module consisting of LiFePO4 battery cells.</p>

Energy storage systems with many Lithium Ion battery cells per string require sophisticated balancing hardware due to individual cells having manufacturing inconsistencies, different self discharge rates, internal resistances and temperature variations. For capacity maximization, safe operation, and extended lifetime, battery balancing is required. Redistributive Non-Dissipative balancing further improves the pack capacity and efficiency over a Dissipative approach where energy is wasted as heat across shunt resistors. Redistribution techniques dynamically shuttle charge to and from weak cells during operation such that all of the stored energy in the stack is utilized. This thesis identifies and develops different balancing control methods. These methods include a unconstrained optimization problem using a Linear Quadratic Regulator (LQR) and a constrained optimization problem using Model Predictive Control (MPC). These methods are benchmarked against traditional rule based (RB) balancing. The control systems are developed using MATLAB/Simulink and validated experimentally on a multiple transformer individual cell to stack topology. The implementation uses a DC2100A Demo-board from Linear Technology with bi-directional flyback converters to transfer the energy between the cells. The results of this thesis show that the MPC control method has the highest balancing efficiency and minimum balancing time. / Thesis / Master of Applied Science (MASc)