An Investigation into the Viability of Battery Technologies for Electric Buses in the UK

This study explores the feasibility of integrating battery technology into electric buses, addressing the imperative to reduce carbon emissions within the transport sector. A comprehensive review and analysis of diverse literature sources establish the present and prospective landscape of battery electric buses within the public transportation domain. Existing battery technology and infrastructure constraints hinder the comprehensive deployment of electric buses across all routes currently served by internal combustion engine counterparts. However, forward-looking insights indicate a promising trajectory with the potential for substantial advancements in battery technology coupled with significant investments in charging infrastructure. Such developments hold promise for electric buses to fulfill a considerable portion of a nation’s public transit requirements. Significant findings emphasize that electric buses showcase considerably lower emissions than fossil-fuel-driven counterparts, especially when operated with zero-carbon electricity sources, thereby significantly mitigating the perils of climate change

The Great Automotive Industry Transformation Following the Immediate Era of Electric Vehicles in Indonesia

In 2030, more than 14 countries and 20 cities will prohibit the sale of fossil (diesel) vehicles. England begins as a figure of support for the Green Revolution in 2030, with the goal of reducing emissions by 2050. While Canada, Japan, and China respond in 2035, Germany goes even further, prohibiting the use and sale in 2035. The United States, China, Dubai, and India are all competing to announce that diesel cars will be banned beginning in 2035. As in this case, it will be fascinating to see how conflict resolution works between fossil car manufacturers (diesel) and electric car manufacturers such as Tesla. Even Toyota's founder, Akio Toyoda, who has yet to find a replacement, openly opposes government policies, Electric vehicles (EV), in his opinion, will harm the environment. a lot bigger than before President Jokowi's attitude and decision towards KBL (Electricity-Based Vehicles) in Indonesia is very clear and focuses on the fact that diesel-based vehicles must gradually be abandoned and replaced with electricity, given the impact of pollution, which is already difficult to control. President Jokowi's directive was delivered in 2020 in the grand ballroom of The Ritz Carlton Pacific Place (PP) Jakarta, as reported by CNN under the headline "Jokowi's Directions, the New Exclusive Capital for Autonomous Electric Vehicles." It will be interesting to see how the government and the automotive industry prepare to respond to the president's new policy to become a strong questioning force that will be the focus of this paper. From the assessment carried out, the country is of great to become one of EV leaders in the World due to skill labors advantages as well as abundant natural resources to support EV manufacturing in Indonesia. Keywords: Car Transformation, Automotive Industry, E

DC Microgrid Modeling and Control in Islanded Mode

Microgrid is new emerging power distribution infrastructures, in smart grid architectures that has the potential to solve major problems arising from distributed generation. Microgrid is defined as the cluster of multiple distributed generators (DGs) that supply electrical energy to consumers with lower power loss. The realization of demand response, efficient energy management, high capability of Distributed Energy Resources (DERs), and high-reliability of electricity delivery leads to a successful Microgrid. In this thesis, DC Microgrid in islanded mode was modelled and controlled and its performance is tested for 24 hours period. The different distributed energy generation systems used are photovoltaic (PV) system, battery energy storage (BESS) system and fuel cell (FC). PV system is modelled by calculating series and shunt resistances of the real life equivalent circuit of the Solar Cell. Four experiments were performed in the Smart Energy lab, RIT Dubai, for the PV systems, to calculate open circuit voltage and short circuit current, to plot the IV characteristics of the PV system, and to track the maximum power point at different irradiances and calculating the daily irradiances. FC modeling was performed in Simulink, the fuel flow was controlled by the output current of the FC to reach the nominal current of 133.3 A and nominal voltage of 45 V. Lithium Ion batteries were used for storing energy generated by the PV system when the supply power exceeds the demand power. Demand power was estimated as the usual daily demand for 24 hours. Controlling these generation systems is performed using converters. Boost Converter used for the PV system was controlled by Maximum Power Point Tracking (MPPT) incremental conductance algorithm to maintain a constant voltage of 300 V at the DC bus despite daily change of the solar power in a day. Boost Buck converter is used to control the charging and discharging processes of the BESS to maintain a constant voltage at the input terminals of the battery to charge it at 130 V and a constant voltage at the DC bus. Boost Converter used for the FC maintained a constant voltage of 100 V

Non-Invasive Estimation of Lithium-Ion Cell Thermo-Physical Properties

Cylindrical Li-ion cells have one of the highest energy density and power density of all Li-ion cell types and typically employ a spiral electrode assembly. This spiral assembly leads to a large anisotropy leading to a drastic difference in the thermo-physical properties in the axial and the radial direction. The radial direction has multiple layers of electrodes and separators leading to a high thermal impedance in this direction, whereas in the axial direction, not many obstacles are present and hence the thermal conductivity is on the higher side. This research describes a novel experimental technique to measure the anisotropic thermal conductivity and heat capacity of Li-ion cells using thermal impedance spectroscopy (T.I.S). It is paramount to experimentally measure the radial and axial thermal conductivities of a cylindrical Li-ion cell because the assumption of isotropic thermal transport properties in Li-ion cell design would lead us to either under predict the value or over predict the value of the temperature field - both of which would lead to highly undesirable results. The experimental measurements indicate that radial thermal conductivity is two orders of magnitude lower than axial thermal conductivity for cylindrical 18650 cells which is in sync to what we intuited. Moreover, the work presented here also establishes a trend of the change in thermos-physical properties with varying the state of charge of the cell. This is extremely helpful in order to develop an efficient cooling system for any device that needs to continuously charge and discharge over thousands of cycles. The data helps to account for the change in the thermal conductivity and heat capacity over a period of cycling of the cell and thus encouraging an update in the cooling system for the device also in order to avoid hazardous situations such as thermal runaway. Lastly, the technique presented in this research is a non-invasive, robust, quick and extremely economical way to determine the thermos-physical properties of an 18650 lithium-ion cell. It also determines the change in thermos-physical properties with the changing state of health of the cell

Scheduling Allocation and Inventory Replenishment Problems Under Uncertainty: Applications in Managing Electric Vehicle and Drone Battery Swap Stations

In this dissertation, motivated by electric vehicle (EV) and drone application growth, we propose novel optimization problems and solution techniques for managing the operations at EV and drone battery swap stations. In Chapter 2, we introduce a novel class of stochastic scheduling allocation and inventory replenishment problems (SAIRP), which determines the recharging, discharging, and replacement decisions at a swap station over time to maximize the expected total profit. We use Markov Decision Process (MDP) to model SAIRPs facing uncertain demands, varying costs, and battery degradation. Considering battery degradation is crucial as it relaxes the assumption that charging/discharging batteries do not deteriorate their quality (capacity). Besides, it ensures customers receive high-quality batteries as we prevent recharging/discharging and swapping when the average capacity of batteries is lower than a predefined threshold. Our MDP has high complexity and dimensions regarding the state space, action space, and transition probabilities; therefore, we can not provide the optimal decision rules (exact solutions) for SAIRPs of increasing size. Thus, we propose high-quality approximate solutions, heuristic and reinforcement learning (RL) methods, for stochastic SAIRPs that provide near-optimal policies for the stations. In Chapter 3, we explore the structure and theoretical findings related to the optimal solution of SAIRP. Notably, we prove the monotonicity properties to develop fast and intelligent algorithms to provide approximate solutions and overcome the curses of dimensionality. We show the existence of monotone optimal decision rules when there is an upper bound on the number of batteries replaced in each period. We demonstrate the monotone structure for the MDP value function when considering the first, second, and both dimensions of the state. We utilize data analytics and regression techniques to provide an intelligent initialization for our monotone approximate dynamic programming (ADP) algorithm. Finally, we provide insights from solving realistic-sized SAIRPs. In Chapter 4, we consider the problem of optimizing the distribution operations of a hub using drones to deliver medical supplies to different geographic regions. Drones are an innovative method with many benefits including low-contact delivery thereby reducing the spread of pandemic and vaccine-preventable diseases. While we focus on medical supply delivery for this work, it is applicable to drone delivery for many other applications, including food, postal items, and e-commerce delivery. In this chapter, our goal is to address drone delivery challenges by optimizing the distribution operations at a drone hub that dispatch drones to different geographic locations generating stochastic demands for medical supplies. By considering different geographic locations, we consider different classes of demand that require different flight ranges, which is directly related to the amount of charge held in a drone battery. We classify the stochastic demands based on their distance from the drone hub, use a Markov decision process to model the problem, and perform computational tests using realistic data representing a prominent drone delivery company. We solve the problem using a reinforcement learning method and show its high performance compared with the exact solution found using dynamic programming. Finally, we analyze the results and provide insights for managing the drone hub operations

A Review of Lithium-Ion Battery Fire Suppression

Lithium-ion batteries (LiBs) are a proven technology for energy storage systems, mobile electronics, power tools, aerospace, automotive and maritime applications. LiBs have attracted interest from academia and industry due to their high power and energy densities compared to other battery technologies. Despite the extensive usage of LiBs, there is a substantial fire risk associated with their use which is a concern, especially when utilised in electric vehicles, aeroplanes, and submarines. This review presents LiB hazards, techniques for mitigating risks, the suppression of LiB fires and identification of shortcomings for future improvement. Water is identified as an efficient cooling and suppressing agent and water mist is considered the most promising technique to extinguish LiB fires. In the initial stages, the present review covers some relevant information regarding the material constitution and configuration of the cell assemblies, and phenomenological evolution of the thermal runaway reactions, which in turn can potentially lead to flaming combustion of cells and battery assemblies. This is followed by short descriptions of various active fire control agents to suppress fires involving LiBs in general, and water as a superior extinguishing medium in particular. In the latter parts of the review, the phenomena associated with water mist suppression of LiB fires are comprehensively reviewed

Electric Vehicles: V2G for Rapid, Safe, and Green EV Penetration

Low carbon and renewable energy sources (RESs) are fast becoming a key sustainable instrument in meeting the global growth of electricity demand while curbing carbon emissions. For example, the gradual displacement of fossil-fuelled vehicles with electrically driven counterparts will inevitably increase both the power grid baseload and peak demand. In many developed countries, the electrification process of the transport sector has already started in tandem with the installation of multi-GW renewable energy capacity, particularly wind and solar, huge investment in power storage technology, and end-user energy demand management. The expansion of the Electric Vehicle (EV) market presents a new opportunity to create a cleaner and transformative new energy carrier. For instance, a managed EV battery charging and discharging profile in conjunction with the national grid, known as the Vehicle-to-Grid system (V2G), is projected to be an important mechanism in reducing the impact of renewable energy intermittency. This paper presents an extensive literature review of the current status of EVs and allied interface technology with the power grid. The main findings and statistical details are drawn from up-to-date publications highlighting the latest technological advancements, limitations, and potential future market development. The authors believe that electric vehicle technology will bring huge technological innovation to the energy market where the vehicle will serve both as a means of transport and a dynamic energy vector interfacing with the grid (V2G), buildings (V2B), and others (V2X)