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With the development of vehicles equipped with automated driving systems, the need for systematic evaluation of AV performance has grown increasingly imperative. According to ISO 34502, one of the safety test objectives is to learn the minimum performance levels required for diverse scenarios. To address this need, this paper combines two essential methodologies - scenario-based testing procedures and scoring systems - to systematically evaluate the behavioral competence of AVs. In this study, we conduct comprehensive testing across diverse scenarios within a simulator environment following Mcity AV Driver Licensing Test procedure. These scenarios span several common real-world driving situations, including BV Cut-in, BV Lane Departure into VUT Path from Opposite Direction, BV Left Turn Across VUT Path, and BV Right Turn into VUT Path scenarios.

Prior work in the literature have shown that pre-chamber spark plug technologies can provide remarkable improvements in engine performance. In this work, three passively fueled pre-chamber spark plugs with different pre-chamber geometries were investigated using in-cylinder high-speed imaging of spectral emission in the visible wavelength region in a single-cylinder direct-injection spark-ignition gasoline engine. The effects of the pre-chamber spark plugs on flame development were analyzed by comparing the flame progress between the pre-chamber spark plugs and with the results from a conventional spark plug. The engine was operated at fixed conditions (relevant to federal test procedures) with a constant speed of 1500 revolutions per minute with a coolant temperature of 90 oC and stoichiometric fuel-to-air ratio. The in-cylinder images were captured with a color high-speed camera through an optical insert in the piston crown.

Nyquist plots are a classical means to visualize a complex vibration frequency response function. By graphing the real and imaginary parts of the response, the dynamic behavior in the vicinity of resonances is emphasized. This allows insight into how modes are coupling, and also provides a means to separate the modes. Mathematical models such as Nyquist analysis are often embedded in frequency analysis hardware. While this speeds data collection, it also removes this visually intuitive tool from the engineer’s consciousness. The behavior of a single degree of freedom system will be shown to be well described by a circle on its Nyquist plot. This observation allows simple visual examination of the response of a continuous system, and the determination of quantities such as modal natural frequencies, damping factors, and modes shapes. Vibration test data from an auto rickshaw chassis are used as an example application.

An experimental investigation of non-intrusive combustion sensing was performed using a tri-axial accelerometer mounted to the engine block of a small-bore high-speed 4-cylinder compression-ignition direct-injection (CIDI) engine. This study investigates potential techniques to extract combustion features from accelerometer signals to be used for cycle-to-cycle engine control. Selection of accelerometer location and vibration axis were performed by analyzing vibration signals for three different locations along the block for all three of the accelerometer axes. A magnitude squared coherence (MSC) statistical analysis was used to select the best location and axis. Based on previous work from the literature, the vibration signal filtering was optimized, and the filtered vibration signals were analyzed. It was found that the vibration signals correlate well with the second derivative of pressure during the initial stages of combustion.

A wet clutch continues to play a critical role for step-ratio automatic transmissions and finds new utilities in hybrid and electrified propulsion systems. A torque transfer function is often employed in practice for sophisticated clutch slip controls. It provides a simple, yet practical framework to represent clutch torque as a function of actuator force. An accurate transfer function is also increasingly desired in today's vehicle design process to enable upfront assessment of clutch controls through simulations. The most common approach is based on Coulomb's linear friction model, where the coefficients are adaptively identified based on vehicle data. However, it is generally difficult to tune Coulomb's model for hydrodynamic behaviors even if the reference vehicle data are available. It also remains a challenge to produce in-vehicle clutch behaviors on a component test bench to determine realistic transfer function before prototype vehicles are built.

The investigation and measurement of particle emissions from foundation brakes require the use of a special adaptation of inertia dynamometer test systems. To have proper measurements for particle mass and particle number, the sampling system needs to minimize transport losses and reduce residence times inside the brake enclosure. Existing models and spreadsheets estimate key transport losses (diffusion, turbophoretic, contractions, gravitational, bends, and sampling isokinetics). A significant limitation of such models is that they cannot assess the turbulent flow and associated particle dynamics inside the brake enclosure; which are anticipated to be important. This paper presents a Design of Experiments (DOE) approach using Computational Fluid Dynamics (CFD) to predict the flow within a dynamometer enclosure under relevant operating conditions. The systematic approach allows the quantification of turbulence intensity, mean velocity profiles, and residence times.

The Hybrid Finite Element Analysis (HFEA) method is based on combining conventional Finite Element Analysis (FEA) with analytical solutions and energy methods for mid-frequency computations. The method is appropriate for computing the vibration of structures which are comprised by stiff load bearing components and flexible panels attached to them; and for considering structure-borne loadings with the excitations applied on the load bearing members. In such situations, the difficulty in using conventional FEA at higher frequencies originates from requiring a very large number of elements in order to capture the flexible wavelength of the panel members which are present in a structure. In the HFEA the conventional FEA model is modified by de-activating the bending behavior of the flexible panels in the FEA computations and introducing instead a large number of dynamic impedance elements for representing the omitted bending behavior of the panels.

High-Reynolds number turbulent boundary layers are an important source for inducing structural vibration. Small geometric features of a structure can generate significant turbulence that result in structural vibration. In this work we develop a new method to couple a high-fidelity fluid solver with a dynamic hybrid analytical-numerical formulation for the structure. The fluid solver uses the Large-Eddy Simulation closure for the unresolved turbulence. Specifically, a local and dynamic one-equation eddy viscosity model is employed. The fluid pressure fluctuation on the structure is mapped to the dynamic structural model. The plate where the flow excitation is applied is considered as part of a larger structure. A hybrid approach based on the Component Mode Synthesis (CMS) is used for developing the new hybrid formulation. The dynamic behavior of the plate which is excited by the flow is modeled using finite elements.

Motion sickness in road vehicles may become an increasingly important problem as automation transforms drivers into passengers. The University of Michigan Transportation Research Institute has developed a vehicle-based platform to study motion sickness in passenger vehicles. A test-track study was conducted with 52 participants who reported susceptibility to motion sickness. The participants completed in-vehicle testing on a 20-minute scripted, continuous drive that consisted of a series of frequent 90-degree turns, braking, and lane changes at the U-M Mcity facility. In addition to quantifying their level of motion sickness on a numerical scale, participants were asked to describe in words any motion-sickness-related sensations they experienced.

Flow control devices can enable vehicle drag reduction through the mitigation of separation and by modifying local and global flow features. Passive vortex generators (VG) are an example of a flow control device that can be designed to re-energize weakly-attached boundary layers to prevent or minimize separation regions that can increase drag. Accurate numerical simulation of such devices and their impact on the vehicle aerodynamics is an important step towards enabling automated drag reduction and shape optimization for a wide range of vehicle concepts. This work demonstrates the use of an open-source computational-fluid dynamics (CFD) framework to enable an accurate and robust evaluation of passive vortex generators in support of vehicle drag reduction. Specifically, the backlight separation of the Ahmed body with a 25° slant is used to evaluate different turbulence models including variants of the RANS, DES, and LES formulations.

To advance vehicle lightweighting, chopped carbon fiber sheet molding compound (SMC) is identified as a promising material to replace metals. However, there are no effective tools and methods to predict the mechanical property of the chopped carbon fiber SMC due to the high complexity in microstructure features and the anisotropic properties. In this paper, a Representative Volume Element (RVE) approach is used to model the SMC microstructure. Two modeling methods, the Voronoi diagram-based method and the chip packing method, are developed to populate the RVE. The elastic moduli of the RVE are calculated and the two methods are compared with experimental tensile test conduct using Digital Image Correlation (DIC). Furthermore, the advantages and shortcomings of these two methods are discussed in terms of the required input information and the convenience of use in the integrated processing-microstructure-property analysis.

Intermediate shaft assembly is used to connect steering gear to the steering wheel. The primary function of the intermediate shaft is to transfer torsional loads. There is a high probability of noise propagating through the Intermediate shaft to the driver. The current standard for measuring the noise is by performing vehicle level subjective evaluations. If improperly clamped at either of the yokes, a sudden change in the direction of the torsional load on the Intermediate shaft can generate a displeasing noise. Noise can also be generated from the constant velocity joint. Intermediate shaft noise can be measured using a microphone or can be correlated to acceleration values. The benefit of measuring the acceleration over sound pressure level is the reduction of complexity of the test environment and test set up. The nature of the noise in question requires the filtering of low frequency data. This paper presents a new test procedure that has been developed by General Motors.

A comprehensive and systematic investigation of the acoustical performance of carbon-nanotube-enhanced polyurethane (PU) foams was performed. The complete foam making process was carried out carefully in order to create stable foams to be integrated with many carbon nanotube materials. A total of eight design parameters were evaluated. Both normal incidence sound transmission loss (STL) and absorption coefficient were measured by use of an impedance tube. It was found that there is an optimum value for most of the design parameters. In general, nanotube-enhanced PU foam definitely demonstrated improvements in both absorption coefficients and sound transmission loss. The improvement of absorption could reach up to 14% and the improvement in STL was quite substantial, i.e. up to 97.5%. This significant improvement in STL with a better absorption coefficient could represent a potential breakthrough in acoustical PU foam manufacturing.

The components in a hybrid electric vehicle (HEV) powertrain include the battery pack, an internal combustion engine, and the electric machines such as motors and possibly a generator. These components generate a considerable amount of heat during driving cycles. A robust thermal management system with advanced controller, designed for temperature tracking, is required for vehicle safety and energy efficiency. In this study, a hybridized mid-size truck for military application is investigated. The paper examines the integration of advanced control algorithms to the cooling system featuring an electric-mechanical compressor, coolant pump and radiator fans. Mathematical models are developed to numerically describe the thermal behavior of these powertrain elements. A series of controllers are designed to effectively manage the battery pack, electric motors, and the internal combustion engine temperatures.

A numerical study is conducted to investigate the effect of changing engine oil and automatic transmission fluid (ATF) temperatures on the fuel economy during warm-up period. The study also evaluates several fuel economy improving devices that reduce the warm-up period by utilizing recycled exhaust heat or an electric heater. A computer simulation model has been developed using a multi-domain 1-D commercial software and calibrated using test data from a passenger vehicle equipped with a 2.4 / 4-cylinder engine and a 6-speed automatic transmission. The model consists of sub-models for driver, vehicle, engine, automatic transmission, cooling system, engine oil circuit, ATF circuit, and electrical system. The model has demonstrated sufficient sensitivity to the changing engine oil and ATF temperatures during the cold start portion of the Federal Test Procedure (FTP) driving cycle that is used for the fuel economy evaluation.

The Energy Finite Element Analysis (EFEA) has been developed for computing the structural vibration and the interior noise level of complex structural-acoustic systems by solving numerically governing differential equations with energy densities as primary variables. In this paper a complete simulation process for evaluating airborne noise in an automotive vehicle is presented and validated through extensive comparison to test data. The theoretical elements associated with the important paths of the noise transfer from the exterior of the vehicle to the interior acoustic space are discussed. The steps required for developing an EFEA model for a vehicle are presented. The model is developed based on the physical construction of the vehicle system and no test measurements are utilized for adjusting the numerical model.

Acoustical materials are widely used in automotive vehicles and other industrial applications. Two important parameters namely Sound Transmission Loss (STL) and absorption coefficient are commonly used to evaluate the acoustical performance of these materials. Other parameters, such as insertion loss, noise reduction, and loss factors are also used to judge their performance depending on the application of these materials. A systematic comparative study of STL and absorption coefficient was conducted on various porous acoustical materials. Several dozen materials including needled cotton fiber (shoddy) and foam materials with or without barrier/scrim were investigated. The results of STL and absorption coefficient are presented and compared. As expected, it was found that most of materials are either good in STL or good in absorption. However, some combinations can achieve a balance of performance in both categories.

This paper proposes a framework to perform design optimization of a series PHEV and investigates the impact of using real-world driving inputs on final design. Real-World driving is characterized from a database of naturalistic driving generated in Field Operational Tests. The procedure utilizes Markov chains to generate synthetic drive cycles representative of real-world driving. Subsequently, PHEV optimization is performed in two steps. First the optimal battery and motor sizes to most efficiently achieve a desired All Electric Range (AER) are determined. A synthetic cycle representative of driving over a given range is used for function evaluations. Then, the optimal engine size is obtained by considering fuel economy in the charge sustaining (CS) mode. The higher power/energy demands of real-world cycles lead to PHEV designs with substantially larger batteries and engines than those developed using repetitions of the federal urban cycle (UDDS).

This paper proposes a simulation based methodology to assess plug-in hybrid vehicle (PHEV) behavior over 24-hour periods. Several representative 24-hour missions comprise naturalistic cycle data and information about vehicle resting time. The data were acquired during Filed Operational Tests (FOT) of a fleet of passenger vehicles carried out by the University of Michigan Transportation Research Institute (UMTRI) for safety research. Then, PHEV behavior is investigated using a simulation with two different charging scenarios: (1) Charging overnight; (2) Charging whenever possible. Charging/discharging patterns of the battery as well as trends of charge depleting (CD) and charge sustaining (CS) modes at each scenario were assessed. Series PHEV simulation is generated using Powertrain System Analysis Toolkit (PSAT) developed by Argonne National Laboratory (ANL) and in-house Matlab codes.

The hybrid FEA method combines the conventional FEA method with the energy FEA (EFEA) for computing the structural vibration in vehicle structures when the excitation is applied on the load bearing stiff structural members. Conventional FEA models are employed for modeling the behavior of the stiff members in the vehicle. In order to account for the effect of the flexible members in the FEA analysis, appropriate damping and spring/mass elements are introduced at the connections between stiff and flexible members. Computing properly the values of these damping and spring/mass elements is important for the overall accuracy of the computations. Utilizing in these computations the analytical solutions for the driving point impedance of infinite or semi-infinite members introduces significant approximations.