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Lithium-ion batteries (LIBs) have been widely used as the energy storage system in plug-in hybrid electric vehicles (PHEVs) and battery electric vehicles (BEVs) due to their high power and energy density and long cycle life compared to other chemistries. However, LIBs are sensitive to operating conditions, including temperature, current demand and surface pressure of the cell. One very well understood phenomenon of lithium-ion battery is the reduction in charge capacity over time due to cycling and storage commonly known as capacity fade. Considering the need for predicting the behavior of an aged cell and the need for estimating battery useful life for warranty purpose, it is crucial to predict the capacity fade with reasonable accuracy. To accommodate this need, a novel cell level empirical aging model is built based on storage tests and cycle tests. The storage test captures the calendar aging of the lithium-ion cell while the cycle test estimates the cycle aging of the cell.

Nowadays, the vehicle design is highly ruled by the increasing customer demands and expectations. In addition to ride comfort and vehicle handling, the Noise, Vibration and Harshness (NVH) behavior of the powertrain is also a critical factor that has a big impact on the customer experience. To evaluate the powertrain NVH characteristics, the NVH error states should be studied. A typical NVH event could be decoupled into 3 parts: source, path, and receiver. Take-off shudder, which evaluates the NVH severity level during vehicle take-off, is one of the most important NVH error states. The main sources of Front Wheel Drive (FWD) take-off shudder are the plunging Constant Velocity Joints (CVJ) on the left and right half shafts. This is because a plunging CVJ generates a third order plunging force with half shaft Revolution Per Minute (RPM), which is along the slip of the plunging CVJ.

One Dimensional models for front end air flows through the cooling system package are very useful for evaluating the effects of component and front end geometry changes. To solve such models for the air flow requires a robust iterative process that involves a number of non-linear sub-models. The cooling fan (s) constitute a major part of the difficulty, especially when they employ a viscous or “thermal” fan drive. This drive varies the torque coupling between the input and output shafts based on the radiator outlet air temperature. The coupling is achieved by viscous shear between two grooved disks and is regulated by a bimetal strip valve that varies the amount of fluid between the disks. This paper presents a mathematical model by which the input/output speed ratio may be determined as a function of the air temperature and input speed. Coefficients in the model are estimated from standard supplier performance information.

Buffeting is a wind noise of high intensity and low frequency in a moving vehicle when a window or sunroof is open and this noise makes people in the passenger compartment very uncomfortable. In this paper, side window buffeting was simulated for a typical SUV using the commercial CFD software Fluent 6.0. Buffeting frequency and intensity were predicted in the simulations and compared with the corresponding experimental wind tunnel measurement. Furthermore, the effects of several parameters on buffeting frequency and intensity were also studied. These parameters include vehicle speed, yaw angle, sensor location and volume of the passenger compartment. Various configurations of side window opening were considered. The effects of mesh size and air compressibility on buffeting were also evaluated. The simulation results for some baseline configurations match the corresponding experimental data fairly well.

Nonlinear finite element crash simulation was used to evaluate convertible crashworthiness in frontal and rear impacts. Simulations were employed to help identify direction for front structure reinforcement and convertible top design. The analyses were performed using LS-Dyna3d on supercomputer and workstation platforms wherever it deemed proper. It demonstrated that the simulations were effective in suggesting the right alternatives, which was later verified in the experimental run.