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.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:723667 |
| Date | January 2017 |
| Creators | Fekete, P. L. |
| Publisher | Coventry University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://curve.coventry.ac.uk/open/items/ea965735-b09d-4ebb-9fc8-e2533bece313/1 |
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