Accurate evaluation of vehicles' transient total power requirement helps achieving further improvements in vehicle fuel efficiency. When operated, the air-conditioning (A/C) system is the largest auxiliary load on a vehicle, therefore accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation models, such as "Autonomie", have been used by OEMs to evaluate vehicles' energy performance. However, the load from the A/C system on the engine or on the energy storage system has not always been modeled in sufficient detail. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software MATLAB/Simulink® is frequently used by vehicle controls engineers to develop new and more efficient vehicle energy system controls. A MATLAB/Simulink-based transient A/C system simulation model is easier to incorporate into MATLAB/Simulink-based vehicle simulation software; therefore, the availability of a transient A/C system simulation tool developed in the MATLAB/Simulink platform is important.NREL has recently developed an A/C simulation tool to address these needs. This paper describes in detail the modeling methods used for this new simulation tool. Comparison with measured data is provided to demonstrate the validity of the model. The agreement between simulation and measurement was shown to be good on both the component and system level. The capabilities of the model are also demonstrated by the example of simulating the SC03 cycle.

A transonic turbine airfoil design is optimized using an artificial intelligence engineering design shell coupled with an inviscid, adaptive grid, CFD solver. The objective of the optimization is to minimize the downstream static pressure variation resulting from the trailing edge shock structure. Cascade test results verify the analytical predictions. Techniques are described which were used to couple the optimization shell to the 2-D turbine airfoil shape to allow the search for optimal designs and indicate the quality of those designs. The emphasis of the discussion is upon the application of these techniques rather than the physical details of the resulting blade design. NOMENCLATURE

The operation of air conditioning (A/C) systems is a significant contributor to the total amount of fuel used by light-and heavy-duty vehicles. Therefore, continued improvement of the efficiency of these mobile A/C systems is important. Numerical simulation has been used to reduce the system development time and to improve the electronic controls, but numerical models that include highly detailed physics run slower than desired for carrying out vehicle-focused drive cycle-based system optimization. Therefore, faster models are needed even if some accuracy is sacrificed.In this study, a validated model with highly detailed physics, the "Fully-Detailed" model, and two models with different levels of simplification, the "Quasi-Transient" and the "Mapped

In this paper, we are going to describe the solutions of the functional equationconcerning the unknown functions ϕ and f defined on an open interval. In our main result only the continuity of the function ϕ and a regularity property of the set of zeroes of f are assumed. As application, we determine the solutions of the functional equationunder monotonicity and differentiability conditions on the unknown functions F,

Electric vehicles (EVs) need highly optimized thermal management systems to improve range. Climate control can reduce vehicle efficiency and range by more than 50%. Due to the relative shortage of waste heat, heating the passenger cabin in EVs is difficult. Cabin cooling can take a high portion of the energy available in the battery. Compared to internal combustion engine-driven vehicles, different heating methods and more efficient cooling methods are needed, which can make EV thermal management systems more complex. More complex systems typically allow various alternative modes of operation that can be selected based on driving and ambient conditions. A good system simulation tool can greatly reduce the time and expense for developing these complex systems. A simulation model should also be able to efficiently co-simulate with vehicle simulation programs, and should be applicable for evaluating various control algorithms. The MATLAB/Simulink dynamic system simulation environment, widely used in the automotive industry, effectively meets these criteria. To model the full EV thermal management system, the National Renewable Energy Laboratory's airconditioning model now incorporates liquid-coolant system components. In the full system model, lookup tables were used to characterize the components' performance. Predicted data obtained with the system simulation model were compared against experimental data. An agreement within 5% for most of the system parameters was achieved. The validated system model was then used to determine which of two possible locations for the power electronics and electric motor in the system is better for quick cabin heating starting from cold soak.