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The introduction of more stringent emission regulatory standards, such as China 6 and Euro 6, with test cycles that are more representative of real-world driving, from WLTP to RDE presents significant challenges to the emission development of internal combustion engine program. In the typical development process, the emission development requires complex work such as after-treatment development and calibration optimizations. In addition, it is late in the process, after the prototype vehicle that is more representative of the production status is ready. To address the situation outlined above, an Engine-in-the-Loop (EIL) testing methodology is developed at SAIC Motor, to front load part of the emission development work to the engine testbed early in the development stage, in the face of ever compressed vehicle program development time. This methodology is to emulate vehicle operations on the engine testbed. Key techniques are developed to achieve this.

The present paper describes a CAE analysis approach to evaluate the transient cylinder head gasket sealing performance of a turbo charged GDI engine in the bench test development. In this approach, both transient gasket sealing force and gasket wear work are calculated to allow design engineers to find out the root cause of cylinder head gasket leakage failures. In this paper, the details of the method development are described. Firstly how to use and get the cylinder head gasket property are described, which is the basic theory and data for the gasket sealing analysis. A transient heat transfer calculation for accurately simulating the engine thermal shock test is established, which is mapped to the transient gasket sealing calculation as pivotal boundary.

Tire cavity noise of pure electric vehicles is particularly prominent due to the absence of engine noise, which are usually eliminated by adding Helmholtz resonators with arbitrary transversal section to the wheel rims. This paper provides theoretical basis for accurately predicting and effectively improving acoustic performance of wheel resonators. A hybrid finite element method is developed to extract the transversal wavenumbers and eigenvectors, and the mode-matching scheme is employed to determine the transmission loss of the Helmholtz resonator. Based on the accuracy validation of this method, the matching design of the wheel resonators and the optimization method of tire cavity noise are studied. The identification method of the tire cavity resonance frequency is developed through the acoustic modal test. A scientific transmission loss target curve and fitness function are defined according to the noise characteristics.

The conventional radar modeling methods for automotive applications were either function-based or physics-based. The former approach was mainly abstracted as a solution of the intersection between geometric representations of radar beam and targets, while the latter one took radar detection mechanism into consideration by means of “ray tracing”. Although they each has its unique advantages, they were often unrealistic or time-consuming to meet actual simulation requirements. This paper presents a combined geometric and physical modeling method on millimeter-wave radar systems for Frequency Modulated Continuous Wave (FMCW) modulation format under a 3D simulation environment. With the geometric approach, a link between the virtual radar and 3D environment is established. With the physical approach, on the other hand, the ideal target detection and measurement are contaminated with noise and clutters aimed to produce the signals as close to the real ones as possible.

Environmental sensing and perception is one of the key technologies on intelligent driving or autonomous vehicles. As a complementary part to current radar and lidar sensors, ultrasonic sensor has become more and more popular due to its high value to the cost. Different from other sensors mainly based on propagation of electromagnetic wave, ultrasonic sensor possesses some unique features and physical characteristics that bring many merits to autonomous vehicle research, like transparent obstacles and highly reflective surfaces detection. Its low-cost property can further bring down hardware cost to foster widespread use of intelligent driving or autonomous vehicles. To accelerate the development of autonomous vehicle, this paper proposes a high fidelity ultrasonic sensor model based on its physical characteristics, including obstacle detection, distance measurement and signal attenuation.

A Finite Element (FE) model for analysis of the rear row occupant injury assessment parameters in a frontal crash test was developed by using the LSTC Hybrid III 5th percentile FE dummy model. Three cases were studied using three different rear seatbelt retractor configurations, which were as follows: an ordinary retractor without load limiter or pretensioner (Case 1), a retractor with load limiter only (Case 2), and a retractor with load limiter and pretensioner (Case 3). The simulation results of each of these three cases were compared respectively to the results obtained from two frontal 50-kph full rigid barrier impact tests and one sled test. It turned out that the dummy kinematics and injury assessment parameters of the head, neck, chest, pelvis and femurs were all similar between test and simulation in the three cases. Thus, FE simulation models can be used to predict dummy injury assessment parameters.

In order to optimize the 2-stroke uniflow engine performance on vehicle applications, numerical analysis has been introduced, 3D CFD model has been built for the optimization of intake charge organization. The scavenging process was investigated and the intake port design details were improved. Then the output data from 3D CFD calculation were applied to a 1D engine model to process the analysis on engine performance. The boost system optimization of the engine has been carried out also. Furthermore, a vehicle model was also set up to investigate the engine in-vehicle performance.