An optimal gear-shifting strategy for heavy trucks with trade-off study between trip time and fuel economy

© Inderscience Enterprises Ltd. The original source of publication is available at InderScience. Zhao, X. x., Ing, A. h., Azad, N. l., & McPhee, J. (2015). An optimal gear-shifting strategy for heavy trucks with trade-off study between trip time and fuel economy. International Journal of Heavy Vehicle Systems, 22(4), 356–374. https://doi.org/10.1504/IJHVS.2015.073205We show how the fuel efficiency of heavy mining trucks can be improved by optimising the gear-shifting strategy. Using characteristic tests of the diesel engine, a high-fidelity model of a mining truck was built in MapleSim and a consistent low-order model was developed in Matlab. Dynamic programming was used to optimise the low-order model of the specialised off-road 30-tonne truck over a fixed route in a mining area. There were two competing objectives: fuel use and trip time, which were combined in a single objective function using weighting coefficients. A Pareto curve was created to analyse the effect of the weights on the fuel use and trip time. Applying the control strategy obtained from dynamic programming to the high-fidelity model, it is estimated that 40,000 L of fuel can be saved annually for a mine that produces 110 kilotonnes of coal per day

The Villages at 995 East Santa Clara St, San Jose: Energy & Emission Report

Our study uses EnergyPlus simulations to examine whole-building demand and energy end-use profiles for different design options and then uses these outputs to evaluate cost and carbon impacts of each scenario in Xendee, a modeling platform designed to “right size” and balance investments in distributed energy resources (DER). Our results show that efficiency measures are key to meet the ambitious performance metrics for this project; however, most of the technology potential occurs for heating, ventilation and air conditioning (HVAC) or domestic hot water (DHW) loads which are a relatively small portion of a mid-rise multifamily building’s overall energy use. The most meaningful strategies to reduce or shift loads for this building include DHW load shifting, energy recovery ventilation, dynamic ventilation, and ceiling fans. Envelope strategies improve overall annual building performance but become an issue when lower heat loss increases cooling during the critical afternoon peak. Compared to efficient, packaged air source heat pumps, a hydronic heating and cooling system (also serving DHW loads) with thermal energy storage has the best energy performance, highest load shifting capability, and best thermal resilience during outages. But because heating and cooling demands are small and hydronic systems are expensive, the net benefits of thermal energy storage are not substantial. Sizing on-site generation and storage systems to cover the “worst case” outage conditions significantly drives up system size and cost. Even small deviations from 100% coverage (95%, or 99%) can dramatically reduce size and cost without a very meaningful change in resilience