The Sustainability of Integrating Contactless Occasional Charging in Electric Vehicle Material Handling

Electric mobility has developed itself to an option to mitigate air pollution and greenhouse gas emissions in cities same as in intralogistics material handling, while significant advances have been made in the research and development of electric vehicles (EV’s). Along with the major challenge of energy storage, another important factor is the efficient design of system energy supply, transfer and consumption. This has had the effect of fundamentally changing perspectives across the mobility and transportation sector.The overarching aim of this research is to examine the impact and potential of using contactless occasional recharging for non-road Electric Vehicles (nrEV) integrated within a manufacturing line, recognising the need to balance the (sometimes competing) demands of delivering reliable and efficient production while respecting environmental and sustainable needs. The integration of a contactless charging infrastructure targets on a reliable energy supply in process inherent break times without changing or interrupting existing production processes.The research investigations based on the Occasional Charging Station Location Model (OCSLM) provide a set of novel results in reference to the impact from interim battery charging to system`s overall sustainability. The application demonstrated a theoretical increase in usable battery energy of 40% to 60% while realising a reduction potential in battery capacity and system cost of between 5% to 45%. However, the use of contactless power transfer based on a standard energy mix resulted in an increase in CO2 emissions of up to 6.89% revealing a negative impact to overall ecology from the use of this energy transfer system

Optimal Routing in Battery-Powered Vehicles

The increased interest in reducing greenhouse gas emissions has motivated renewed interest in electric vehicles technology as an alternative to current fossil-fuel based transportation equipment. Electric vehicles (EVs) are envisioned as a promising viable technology because of their friendly impact on the environment and higher efficiency over conventional vehicles that rely on fossil fuel. However, the EVs’ limited battery capacity, resulting in limited cruising range and long recharging time, hinders the widespread adoption of EVs. An essential requirement of EV motors is the ability to operate with minimum energy consumption in order to provide at least the same driving range as their Internal Combustion Engine (ICE) counterparts. Energy-optimal routing, which aims to find the least energy consuming routes, under battery constraints has been recognized as a viable approach to prolonging the cruising range of the EV battery. This thesis addresses the problem of optimal routing for EVs and proposes a solution to overcome the difficulties of optimal energy/time routing under battery constraints. A multi-criteria path-finding technique is proposed. The proposed technique functions in two modes and solves the problem of optimal energy/time routing in EVs with worst time complexity of . First, an energy mode to solve the problem of energy-optimal routing under battery constraints is introduced. This mode computes the most energy-efficient route from a source to a destination, thus extending the limited cruising range of a battery. Second, a time mode to solve the problem of optimal travel time routing under battery constraints, by computing the most efficient travel-time route from a source to a destination, is proposed. An EV can operate under these two modes to strike a balance between power consumption and travel time so as to satisfy user constraints and needs. In addition, a technique to reduce the effects of range anxiety on the vehicle operator is proposed. This technique computes a robust estimate of driving range. Furthermore, the technique analyzes an EV’s battery capacity required by the vehicle in order to reach a charging station. The thesis reports experimental work conducted to test and validate the proposed techniques under various driving conditions

An approach to potential evaluation of a contactless energy supply infrastructure for occasional recharging in production related, non-automated material handling

Significant advances have been made in the research and development of electric vehicles (EV’s). Along with the major challenge of energy storage, being also addressed is the efficient design of system energy transfer and consumption. This has had the effect of fundamentally changing perspectives across the mobility and transportation sector. Applied predominantly to road-going vehicles, the industrial context of non-road Electric Vehicles (nrEV’s) and specifically the use of manned electric forklift trucks integrated within the production related materials handling system has, to-date, received far less attention. The overarching aim of this research is to examine the impact and potential for the use of contactless occasional recharging of nrEV’s integrated within a manufacturing line, recognising the need to balance the (sometimes competing) demands of delivering sustainable production while exercising environmental responsibility. Meeting the objectives of this research resulted in the development of a location allocation model for electric charging station determination based on a fundamental understanding of the nature and quality of process inherent key performance indicators (KPI’s) as well as comprehensive process and energy monitoring while considering both Lean and Green Management perspectives. The integration of the generated knowledge and information into a generally valid simulation tool for occasional charging system implementation allows to more thoroughly investigate the impact from occasional charging to overall efficiency and sustainability to be realised. An investigation into relevant literature identified the need for specifically generated energy consumption data and confirmed the need for an energy optimisation model specific to the area of production related materials handling. Empirical data collected from repeated standardised materials handling operations within a selected production related materials handling environment resulted in the development of the Standard Energy Consumption Activity tool (SECA). Further work within this pilot study confirmed the tool as capable of generating reliable and valid data and confirmed the SECA tool as a generally applicable benchmark for energy consumption determination in material handling based on fractional process functions. Integrating this approach into a comprehensive process analysis and charging infrastructure optimisation resulted in the development of an Excel-based simulation model. The (Occasional Charging Station Location Model) OCSLM is based upon Maximal Covering Location Modelling and an endogenous covering distance definition in order to simulate process related potentials and optimal charging system implementation allocations, the target being to increase vehicles usable battery energy. A comprehensive case study based upon six individual and one combined data set confirmed the general and wider applicability of the OCSLM model while the application of the model provides a set of novel results. The application demonstrated a theoretical increase in usable battery energy of between 40% and 60% and within the same case study the impact of technology implementation identified that a reduction in battery and system cost of between 5% and 45% can be realised. However, the use of contactless power transfer resulted in an increase in CO2 emissions of up to 6.89% revealing a negative impact to overall ecology from the use of this energy transfer system. Depending on the availability of fast connecting, contact based energy transmission systems, the approach and results of OCSLM have shown to be directly applicable to contact based systems with resulting CO2 emissions decreasing by 0.94% at an energy transfer efficiency of 96%. Further novelty, of benefit to both academic and industry practice, was realised through the framework and information of the research with the provision of SECA as a process function-based and generally applicable energy consumption standard, OCSLM as a Maximal Covering Location Modell with a focus on occasional charging based on an endogenous covering distance and integrating detailed energy and process monitoring into electric charging station allocation, and the methodology for the application of this approach for fast connecting contactless and contact charging models and cases

Spatial-temporal domain charging optimization and charging scenario iteration for EV

Environmental problems have become increasingly serious around the world. With lower carbon emissions, Electric Vehicles (EVs) have been utilized on a large scale over the past few years. However, EVs are limited by battery capacity and require frequent charging. Currently, EVs suffer from long charging time and charging congestion. Therefore, EV charging optimization is vital to ensure drivers’ mobility. This study first presents a literature analysis of the current charging modes taxonomy to elucidate the advantages and disadvantages of different charging modes. In specific optimization, under plug-in charging mode, an Urgency First Charging (UFC) scheduling policy is proposed with collaborative optimization of the spatialtemporal domain. The UFC policy allows those EVs with charging urgency to get preempted charging services. As conventional plug-in charging mode is limited by the deployment of Charging Stations (CSs), this study further introduces and optimizes Vehicle-to-Vehicle (V2V) charging. This is aim to maximize the utilization of charging infrastructures and to balance the grid load. This proposed reservation-based V2V charging scheme optimizes pair matching of EVs based on minimized distance. Meanwhile, this V2V scheme allows more EVs get fully charged via minimized waiting time based parking lot allocation. Constrained by shortcomings (rigid location of CSs and slow charging power under V2V converters), a single charging mode can hardly meet a large number of parallel charging requests. Thus, this study further proposes a hybrid charging mode. This mode is to utilize the advantages of plug-in and V2V modes to alleviate the pressure on the grid. Finally, this study addresses the potential problems of EV charging with a view to further optimizing EV charging in subsequent studies