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Increasing the operational lifetime and optimising the design of crankcase oil-mist filters. Australia is one of the largest (per capita) users worldwide of heavy diesel engines, within sectors such as transport, mining, construction, shipping and power generation (usage of many of the above is concentrated in regional communities e.g. mining). This work will minimise emissions from such industries, as well as reduce lubricant oil usage - thereby maximising waste oil recovery and reuse (approx 5 ....Increasing the operational lifetime and optimising the design of crankcase oil-mist filters. Australia is one of the largest (per capita) users worldwide of heavy diesel engines, within sectors such as transport, mining, construction, shipping and power generation (usage of many of the above is concentrated in regional communities e.g. mining). This work will minimise emissions from such industries, as well as reduce lubricant oil usage - thereby maximising waste oil recovery and reuse (approx 5500 tonnes p.a.). Oil mists can be regarded as volatile organic compounds (VOCs) for the purposes of CO2 equivalent emissions, so therefore, the efficient capture of oil mists will reduce carbon emissions from the above industries in Australia.Read moreRead less
Analysis and modeling of driving patterns for limited-range electric vehicles. The electrification of the personal transport sector seems to be only a matter of time. It is important to study and model the effects of this sector now, in order to recommend decision makers on issues like standardization and infrastructure planning. Understanding and being able to predict EV driving and charging patterns will allow us to provide planning assistance for:
· Effects of day-time dependent energy pri ....Analysis and modeling of driving patterns for limited-range electric vehicles. The electrification of the personal transport sector seems to be only a matter of time. It is important to study and model the effects of this sector now, in order to recommend decision makers on issues like standardization and infrastructure planning. Understanding and being able to predict EV driving and charging patterns will allow us to provide planning assistance for:
· Effects of day-time dependent energy pricing structure on EV charging behavior
· Optimal energy pricing to encourage off-peak charging
· Optimal number and location of EV charging stations
· Expected uptake of PHEV/EVs depending on petrol, electricity and conversion cost
· Expected additional energy demand for EVs and PHEVs with day-time energy usage pattern
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