Behaviour of Lithium-Ion Batteries in Electric Vehicles

This chapter will discuss the technical requirements and status of applying lithium-ion batteries to electrified vehicles. It will begin by introducing the principles of vehicle propulsion, electrified features, powertrain design, and the resulting battery chemistry applicability. An understanding of vehicle needs will enable a discussion on lithium-ion battery pack design. Once the basic layout of pack design is understood, it is necessary to appropriately size a pack to meet its intended vehicle function relative to various drive cycles and other requirements. A review of current lithium-ion technology and applicability for automotive applications will then follow. This chapter will describe existing cell energy and power performance in the context of international performance targets. The various features of cell design for automotive will also be discussed along with a review of current safety testing standards and regulations. Finally, an examination of existing commercialized products will show how the vehicle, pack and cell design principles described are implemented in actual production vehicles.

Supported by policy, electric vehicles (EVs) powered by lithium batteries are being commercialised in an increasing number of models and their global stock surpassed two million units in 2016. However, there is uncertainty around the future price and availability of lithium, which has consequences on the feasibility of manufacturing lithium batteries at scale. Reaching the EV penetration levels foreseen by governments implies a substantial growth in lithium demand. In this chapter, we review the evidence around future lithium availability for the manufacturing of EV batteries. We examine the methods used to estimate both lithium demand from EVs and lithium supply from brines and ore. The main variables influencing demand are the future size of the EV market, the average battery capacity and the material intensity of the batteries. Supply projections depend on global reserve and resource estimates, forecast production and recyclability. We find that the assumptions made in the literature on the key variables are characterised by significant uncertainty. However based on the available evidence, it appears that lithium production may be on a lower trajectory than demand and would have to rapidly increase in order not to prove a bottleneck to the expansion of the EV market. More research is needed in order to reduce uncertainty on lithium intensity of future EVs and improve understanding of the potential for lithium production expansion and recycling.

The worldwide development and market penetration of electric vehicles (EVs) and hybrid cars has lagged far behind initial expectations and prognoses. However, more recent discussions about petrol and diesel car emissions seem to accelerate the market penetration of battery-based mobility and other alternative options. Many big car manufacturers have announced that they will offer a broad EV fleet by between 2020 and 2024 at the latest, and some even plan to abandon the production of petrol- and diesel-powered cars completely. This might result in a sharp increase in EV market shares and, consequently, in a significant amount of resources needed to produce traction batteries. At present, EVs are produced mainly using different types of Li-ion batteries (LIBs) and only to a lesser extent other battery systems like NiMH. Also in a midterm perspective, LIBs will probably continue to be the preferred energy storage technology for EVs due to their excellent technical performance. This raises the question of whether we will have enough reserves or resources of key metals such as Li, Co, Ni, Cu, Al, Mn or P required for Li-ion traction batteries. In answering this question, a dynamic material flow analysis (dMFA) was conducted to quantify the global demand for these key metals driven by the increasing number of battery vehicles. The calculations also take into account potential recycling of metals from batteries after the use phase, which significantly reduces the pressure on reserves and resources.

Encouraged by the falling cost of batteries, electric vehicle (EV) policy today focuses on accelerating electrification of passenger cars, paying comparatively little attention to the cost of the particular type of EVs and charging infrastructure deployed. This chapter first discusses the strong influence that EV policy design has on the development of particular EV types. It then illustrates recent research conducted by the authors, showing that EV policy with a strong bias towards long-range battery electric vehicles (BEVs) risks leading to higher overall costs in the medium term. The costs could possibly exceed the ability of governments to sustain the necessary incentives and of automotive original equipment manufacturers to internally subsidise EVs until battery cost drops sufficiently. While the research does not fully explore the latter issue and its potential to stall the EV transition, it does show that the incremental cost of different EV and infrastructure mixes over the whole passenger car fleet can differ quite substantially and that promoting a balanced mix of BEVs and plug-in hybrid electric vehicles (PHEVs) may set the electrification of passenger cars on a lower-risk, lower-cost path. Examining EV policy in the UK and in California, we find that it is generally not incompatible with achieving balanced mixes of BEVs and PHEVs; however, it could be better designed if it paid more attention to cost and technology development risk.

The substantial impacts of transportation on environment, society, and economy strongly urge the incorporation of sustainability into transportation planning. Major developments that enhance transportation sustainability include alternative fuels, electric drive and other novel technologies for vehicle propulsion. This chapter presents a sustainability framework that enables the assessment of transportation vehicle characteristics. Identified indicators are grouped into five sustainability dimensions (environment, technology, energy, economy, and users). The method joins life cycle impacts and a set of quantified indicators to assess the sustainability performance of seven popular light-duty vehicles and two types of transit buses. The hybrid diesel electric bus received the highest sustainability index and the internal combustion engine vehicle the lowest. Fuel cell and hybrid electric vehicles were found to have the highest sustainability index among all passenger vehicles. The sustainability performance of some new technologies currently suffers from limitations in engine and battery performance, comfort and convenience, and availability of charging stations.

When the sensors and signals that enable connected and autonomous vehicle (CAV) technology are combined with vehicle electrification, new vehicle control strategies that improve fuel economy (FE) are possible through perception, planning, and a control request issued to the vehicle plant. In this chapter, each CAV technology that could contribute to planning is introduced and discussed. Next, the techniques for modeling and validating a vehicle plant and running controller are discussed. Then, three planning-based control strategies are developed: (1) an Optimal Energy Management Strategy (Optimal EMS), (2) Eco-Driving strategies, and (3) an Optimal EMS combined with Eco-Driving strategies. Each of these planning-based control strategies is evaluated using a validated model of a 2010 Toyota Prius in Autonomie so that engine power, battery state of charge, and FE results can be compared. The results indicate that a 40% + FE improvement is possible when an Optimal EMS is combined with Eco-Driving for city drive cycles. Overall, as more vehicles incorporate CAV technologies and electrification, these FE improvements will be easier to achieve and will have a greater impact on transportation sustainability.

Recent research on electric commercial vehicles (ECVs) has mostly been limited to short-haul applications and single planning perspectives. Especially in mid-haul logistics networks where recharging on routes is necessary, integrated planning approaches become inevitable due to interdependent decisions on network design and vehicle operations. This chapter provides an overview of planning approaches for ECVs that have been presented so far and presents a generic modeling approach for integrated TCO analysis, taking strategic network design and operational vehicle routing and recharging decisions into consideration. This approach is then applied to a real-world case study of a large German retail company. We discuss results with respect to the competitiveness of ECVs compared to ICEVs. Herein, we study economic and ecological benefits. Furthermore, we analyze battery degradation effects from a technical point of view. Results show that ECVs are on the verge of breaking even in mid-haul logistics for certain application cases.

Safety and reliability are the two key challenges for large-scale electrification of road transport sector. Current Li-ion battery packs are prone to failure due to reasons such as continuous transmission of mechanical vibrations, exposure to high impact forces and, thermal runaway. Robust mechanical design and battery packaging can provide greater degree of protection against all of these. This chapter discusses design elements like thermal barrier and gas exhaust mechanism that can be integrated into battery packaging to mitigate the high safety risks associated with failure of an electric vehicle (EV) battery pack. Several patented mechanical design solutions, developed with an aim to increase crashworthiness and vibration isolation in EV battery pack, are discussed. Lastly, mechanical design of the battery pack of the first fully electric bus designed and developed in Australia is presented. This case study showcases the benefits of adopting modularity in the design of EVs. In addition, it highlights the importance of packaging space for EVs, particularly in low-floor electric buses, as weight distribution becomes a challenge in these applications.

Electric vehicles (EVs) have gained considerable attention owing to their excellent characteristics as transportation vehicles and due to their energy storage capacity. Unfortunately, this massive deployment of EVs leads to significantly high electricity demand due to their charging requirements, particularly when they are charged uncoordinatedly. In addition, the concentrated charging of EVs can potentially decrease the quality of electricity, including frequency and voltage, in addition to causing other electrical grid problems. These conditions have motivated the development of technology and policies for minimizing these negative impacts. In this chapter, an advanced quick charging system for EVs that utilizes batteries to support the simultaneous fast charging of EVs has been described, including a description of its performance under different contracted electricity capacities, ambient temperatures (seasons), and high charging demand. In addition, the charging and discharging behaviors of EVs under different ambient temperatures have been explained. Our findings suggest that charging at high ambient temperature (e.g., during summer) allows a significantly higher charging rate than charging performed at low ambient temperature (e.g., during winter). A higher charging rate leads to shorter charging time. Furthermore, the battery-assisted charging system exhibited excellent performance because it enabled optimum quick charging during simultaneous charging in addition to maintaining the contracted electricity of the charger.

Traditional charging technology uses external battery parameters, e.g., terminal voltage and current, as the control target, and only controlling external parameters does not give information on internal characteristics of the battery, and thus, the effects of different charging currents and cutoff voltages on battery degradation are not clear. In this chapter, the electrochemical reaction mechanisms and external characteristics of the battery during charging process are studied, and the mechanisms of battery charging performance and characteristics of charging polarization are revealed. By researching the electrochemical reaction law and potential distribution characteristics of the battery during the charging process, a novel electric model based on the Butler–Volmer equation was employed to outline the unique phenomena induced by changing rates for high-power lithium batteries. The robustness of the developed model under varying loading conditions, including galvanostatic test and Federal Urban Dynamic Schedule (FUDS) test, is evaluated and compared against experimental data. The analysis of polarization voltage features at different charging rates indicates that polarization voltage is high on both ends of the SOC range but low in the middle SOC range, and the shape of the polarization voltage curve is like a bowl. In the middle SOC range, an approximate linear relationship exists between the steady-state polarization voltage and the charging rate. The two time constants (TCs) representing polarization voltage change are in 10- and 1000-s orders of magnitude, respectively, which corresponds to three charging reaction processes. The dynamic polarization voltage exhibits a lagged effect and an overshoot effect when the charge current is changed. Depending on the polarization voltage characteristics, setting battery polarization voltage and charging cutoff voltage as the constraint conditions, the calculation method for the maximum charge current of a Li-ion battery based on the battery polarization time constant is established, which can help engineers design a practical charging strategy. An optimal charging strategy is devised to balance charging time and temperature rise, with polarization constraints fulfilled. The charging target function is constructed by setting limits to the charging temperature rise and shortening the charging time as the optimization target. The optimal charging current curve is determined by the genetic algorithm (GA) under the constraint of the maximum charge current and limited by polarization voltage. The experimental results indicate that the developed charging protocol can reduce charging time remarkably with reasonable temperature rise, highlighting its advantages over conventional CC–CV charging methods. Aging experiments further verify that the developed charging protocol has a similar capacity retention ratio, compared to that of 0.5C CC–CV charging after 700 cycles. By effectively combining the external characteristics and the internal electrochemical reaction during the charging process, the optimized charging strategy with polarization voltage as the control target results in a fast charging process without damage to the battery life.

The battery management system (BMS) plays a critical role in battery packs especially for the lithium-ion battery chemistry. Protecting the cells from overcharge and overdischarge, controlling the temperature at the desired level, prolonging the life of the battery pack, guaranteeing the safety and indicating the available power and energy of the battery are the key functionalities of a BMS. In this chapter, two important concepts of a BMS are discussed: (i) battery state-of-charge (SoC) and (ii) battery state-of-health (SoH). Battery SoC and SoH are variables which should be determined precisely in order to use the battery optimally and safely. Batteries are time-varying systems that behave very differently at various states. In other words, the internal states of a battery tell us what we should expect from it. Depending on the battery chemistry, various techniques have been developed in the literature for SoC and SoH estimation. This covers a wide range from simple integration of current over time (i.e. coulomb counting) to advanced estimation techniques such as Kalman filter. In this study, almost all the existing battery SoC and SoH estimation approaches are reviewed and proper references are cited for further studies in each category.

The introduction of electromobility will lead to a significant increase of waste traction batteries within the next decade. Recycling of these batteries is currently a huge challenge as the necessary legislative framework, logistic concepts, and recycling processes are in an early stage of development. In the first part of this chapter, the legal situation in the largest markets (European Union, People’s Republic of China, and USA) is summarized and a forecast of traction battery return flows for cars and buses until 2025 is presented. The second part discusses the recycling chain including extraction of the batteries from end-of-life (EOL) vehicles, battery disassembly, and different approaches for cell recycling. The focus is on industrial efforts. In addition, economic and ecologic aspects are briefly addressed. The last part summarizes the main conclusions and highlights task fields to close the gaps in lithium-ion battery recycling.

The rapid development of electric vehicles (EVs) has caused a problem for the industry: what happens to the batteries at the end of their useful life in EVs? Repurposing those batteries for a less-demanding second-life application, e.g. stationary energy storage, could provide a potential solution to extract more value than just recycling or disposal. This paper explores the current battery second use (B2U) business models and the key challenges of implementing B2U. Based on empirical interview data from stakeholders involved in B2U, this paper presents a typology of current B2U business models—standard, collaborative and integrative business models—and offers implications for designing business models that incorporate sustainability at the core. The findings also show that innovative business model is a key to addressing the B2U challenges and overcoming the ‘inferiority’ of second-life batteries as used products.