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Lookup tables and functions are widely used in real-time embedded automotive applications to conserve scarce processor resources. To minimize the resource utilization, these lookup tables (LUTs) commonly use custom data structures. The lookup function code is optimized to process these custom data structures. The legacy routines for these lookup functions are very efficient and have been in production for many years. These lookup functions and the corresponding data structures are typically used for calibration tables. The third-party calibration tools are specifically tailored to support these custom data structures. These tools assist the calibrators in optimizing the control algorithm performance for the targeted environment for production. Application software typically contains a mix of both automatically generated software and manually developed code. Some of the same calibration tables may be used in both auto generated and hand-code [ 1 ] [ 2 ].

A mathematical model is presented for analysis and optimization of the adsorbents in the multifiltration beds contained in the International Space Station (ISS) water processor. The model consists of a physical properties database, an equilibrium description for single and multicomponent adsorption, and a kinetic description for adsorption beds in the water processor. The model is verified on a surrogate mixture designed to mimic the adsorption potential of the ISS shower/handwash waste stream.

A mathematical model is presented for analysis and optimization of the ion exchange beds in the International Space Station (ISS) Water Processor. The model consists of a physical properties database, an equilibrium description for binary and multicomponent ion exchange, and a kinetic description for ion exchange beds in the Water Processor. The ion exchange model will be verified for an Ersatz water designed to mimic the ISS shower/handwash waste stream.

The formulation of mathematical model for the computational simulation of transient temperature response and phase change of refrigerant in a vapor condenser of an automotive air conditioning unit is described. A demonstrative computational simulation of a sample air cooled vapor condenser charged with Freon 12 is presented. The computational analysis predicts an initial surge and followed by an oscillation of the condensate outflow rate from the condenser when the air-conditioning unit is started, and the tube length required for complete condensation of inflow vapor is a maximum value at start up. The rise of the temperatures of the condenser tubes and cooling air flow during the start-up and load change operations rate found to be gradual but the scale of these temperature changes are considered small.

The purpose of this study was to investigate the pressure drop and regeneration characteristics of a silicon carbide (SiC) wall-flow diesel particulate filter. The performance of a 25 μm mean pore size SiC dual trap system (DTS) consisting of two 12 liter traps connected in parallel in conjunction with a copper (Cu) fuel additive was evaluated. A comparison between the 25 μm DTS and a 15 μm DTS was performed, in order to show the effect of trap material mean pore size on trap loading and regeneration behavior. A 1988 Cummins LTA 10-300 diesel engine was used to evaluate the performance of the 15 and 25 μm DTS. A mathematical model was developed to better understand the thermal and catalytic oxidation of the particulate matter. For all the trap steady-state loading tests, the engine was run at EPA mode 11 for 10 hours. Raw exhaust samples were taken upstream and downstream of the trap system in order to determine the DTS filtration efficiency.

This paper examines the feasibility of using eigenvalue modification as the effective algorithm for interactive modal analysis. The dynamic characteristics of a cantilever beam are determined experimentally and compared to the results of an analytical study. The model is then modified with the addition of mass and stiffness. The results predicted using eigenvalue modification theory on the analytical model compare very favorably with experimentally determined results.

A study was undertaken to investigate the affect of exhaust gas recirculation (EGR) on engine wear and lubricating oil degradation in a heavy duty diesel engine using a newly developed methodology that uses analytical ferrography in conjunction with short term tests. Laboratory engine testing was carried out on a Cummins NTC-300 Big Cam II diesel engine at rated speed (1800 RPM) and 75% rated load with EGR rates of 0, 5, and 15% using a SAE 15W40 CD/SF/EO-K oil. Dynamometer engine testing involved collecting oil samples from the engine sump at specified time intervals through each engine test. These oil samples were analyzed using a number of different oil analysis techniques that provide information on the metal wear debris and also on the lubricating oil properties. The results from these oil analysis techniques are the basis of determining the effect of EGR on engine wear and lubricating oil degradation, rather than an actual engine tear down between engine tests.

This paper details the computer algorithm which was developed to determine the A/C refrigeration circuit balance point under the system transient operating conditions. The A/C circuit model consisting of major component submodels, such as the evaporator, compressor, condenser, orifice, air handling system, and connecting hoses, are included in the study. Pressure drop and thermal capacity for the evaporator, condenser, and connecting ducts/hoses are also considered in the simulation. The results obtained from the simulation model are in good agreement with the experimental data. Users can take advantage of this CAE tool to optimize the A/C system design and to minimize the development process with time-saving and cost-effective perspectives.

A Computer-Aided Engineering (CAE) model for automobile climate control system is presented to provide engineers with an cost effective analysis tool for designing, developing, and optimizing the vehicle interior climate. It is the objective of this paper to develop a mathematical model which predicts the lumped temperature and lumped humidity variations inside the passenger compartment under design and operating conditions. The transient nature of the passenger cabin temperature, average interior mass temperature, and humidity are modeled using three coupled non-linear ordinary differential equations based on mass and energy balances. These equations are then solved by a fourth-order Runge-Kutta method with adaptive step size control.