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Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel.

Autonomy for multiple trucks to drive in a fixed-headway platoon formation is achieved by adding precision GPS and V2V communications to a conventional adaptive cruise control (ACC) system. The performance of the Cooperative ACC (CACC) system depends heavily on the reliability of the underlying V2V communications network. Using data recorded on precision-instrumented trucks at both ACM and NCAT test tracks, we provide an understanding of various effects on V2V network performance: Occlusions - non-line-of-sight (NLOS) between the Tx and Rx antenna may cause network signal loss. Rain - water droplets in the air may cause network signal degradation. Antenna position - antennas at higher elevation may have less ground clutter to deal with. RF interference - interference may cause network packet loss. GPS outage - outages caused by tree cover, tunnels, etc. may result in degraded performance. Road curvature - curves may affect antenna diversity.

In frontal collision of vehicles, the front bumper system is the first structural member that receives the energy of collision. In low speed impacts, the bumper beam and the crush cans that support the bumper beam are designed to protect the engine and the radiator from being damaged, while at high speed impacts, they are required to transfer the energy of impact as uniformly as possible to the front rails that contributes to the occupant protection. The bumper beam material today is mostly steels and aluminum alloys, but carbon fiber composites have the potential to reduce the bumper weight significantly. In this study, crash performance of bumper beams made of a boron steel, aluminum alloy 5182 and a carbon fiber composite with steel crush cans is examined for their maximum deflection, load transfer to crush cans, total energy absorption and failure modes using finite element analysis.

The article solves the problem of increasing the energy efficiency of the traction electric drive in the low load conditions. The set objective is achieved by analogy with internal combustion engines by decreasing the consumed energy using the amplitude control of the three-phase voltage of the induction machine. The basis of the amplitude control is laid by the constancy criterion of the overload capacity with respect to the electromagnetic torque, which provides a reliable reserve from a "breakdown" of the induction machine mode in a wide range of speeds and loads. The control system of the traction electric drive contains a reference model of electromechanical energy conversion represented by the generalized equations of the instantaneous balance of the active and reactive power and the mechanical load. The induction machine is controlled by two adaptive variables: the electromagnetic torque and the voltage amplitude.

As intelligent automated vehicle technologies evolve, there is a greater need to understand and define the role of the human user, whether completely hands-off (L5) or partly hands-on. At all levels of automation, the human occupant may feel anxious or ill-at-ease. This may reflect as higher stress/workload. The study in this paper further refines how perceived workload may be determined based on occupant physiological measures. Because of great variation in individual personalities, age, driving experiences, gender, etc., a generic model applicable to all could not be developed. Rather, individual workload models that used physiological and vehicle measures were developed.

A ductile failure criterion (DFC), which defines the stretching failure at localized necking (LN) and treats the critical damage as a function of strain path and initial sheet thickness, was proposed in a previous study. In this study, the DFC is revisited to extend the model to the low stress triaxiality domain and demonstrates on modeling forming limit curve (FLC) of TRIP 690. Then, the model is used to predict stretching failure in a finite element method (FEM) simulation on a TRIP 690 steel rectangular cup draw process at room temperature. Comparison shows that the results from this criterion match quite well with experimental observations.

This study presents a methodology for comparative analysis of seat and suspension parameters on a system level to achieve minimum occupant head displacement and acceleration, thereby improving occupant ride comfort. A lumped-parameter full-vehicle ride model with seat structures, seat cushions and five occupants has been used. Two different vehicle masses are considered. A low amplitude pulse signal is provided as the road disturbance input. The peak vertical displacement and acceleration of the occupant’s head due to the road disturbance are determined and used as measures of ride comfort. Using a design of experiments approach, the most critical seat cushion, seat structure and suspension parameters and their interactions affecting the occupant head displacement and acceleration are determined. An optimum combination of parameters to achieve minimum peak vertical displacement and acceleration of the occupant’s head is identified using a response surface methodology.

Corrosion-fatigue (CF) and stress corrosion cracking (SCC) have long been recognized as the major degradation and failure mechanisms of engineering materials under combined mechanical loading and corrosive environments. How to model and characterize these failure phenomena and how to screen, rank, and select materials in corrosion-fatigue and stress corrosion cracking resistance is a significant challenge in the automotive industry and many engineering applications. In this paper, the mathematical structure of a superposition-theory based corrosion-fatigue model is investigated and possible closed-form and approximate solutions are sought. Based on the model and the associated solutions and test results, screening and ranking of the materials in fatigue, corrosion-fatigue are discussed.

Brake squeal is an instability issue with many parameters. This study attempts to assess the effect of thermal load on brake squeal behavior through finite element computation. The research can be divided into two parts. The first step is to analyze the thermal conditions of a brake assembly based on ANSYS Fluent. Modeling of transient temperature and thermal-structural analysis are then used in coupled thermal-mechanical analysis using complex eigenvalue methods in ANSYS Mechanical to determine the deformation and the stress established in both the disk and the pad. Thus, the influence of thermal load may be observed when using finite element methods for prediction of brake squeal propensity. A detailed finite element model of a commercial brake disc was developed and verified by experimental modal analysis and structure free-free modal analysis.

Most of the present electric vehicle (EV) on-board chargers utilize a conventional design, i.e., a boost-type Power Factor Correction (PFC) controller followed by an isolated DC/DC converter. Such design usually yields a ~94% wall-to-battery efficiency and 2~3kW/L power density at most, which makes a high-power charger, e.g., 20kW module difficult to fit in the vehicle. As described in this paper, first, an E-mode GaN HEMT based 7.2kW single-phase charger was built. Connecting three such modules to the three-phase grid allows a three-phase >20kW charger to be built, which compared to the conventional three-phase charger, saves the bulky DC-bus capacitor by using the indirect matrix converter topology. To push the efficiency and power density to the limit, comprehensive optimization is processed to optimize the single-phase module through incorporating the GaN HEMT switching performance and securing its zero-voltage switching.

Recent stringent government regulations on emission control and fuel economy drive the vehicles and their associated components and systems to the direction of lighter weight. However, the achieved lightweight must not be obtained by sacrificing other important performance requirements such as manufacturability, strength, durability, reliability, safety, noise, vibration and harshness (NVH). Additionally, cost is always a dominating factor in the lightweight design of automotive products. Therefore, a successful lightweight design can only be accomplished by better understanding the performance requirements, the potentials and limitations of the designed products, and by balancing many conflicting design parameters. The combined knowledge-based design optimization procedures and, inevitably, some trial-and-error design iterations are the practical approaches that should be adopted in the lightweight design for the automotive applications.

Nowadays, the automotive industry is experiencing the advent of unprecedented applications with connected devices, such as identifying safe users for insurance companies or assessing vehicle health. To enable such applications, driving behavior data are collected from vehicles and provided to third parties (e.g., insurance firms, car sharing businesses, healthcare providers). In the new wave of IoT (Internet of Things), driving statistics and users’ data generated from wearable devices can be exploited to better assess driving behaviors and construct driver models. We propose a framework for securely collecting data from multiple sources (e.g., vehicles and brought-in devices) and integrating them in the cloud to enable next-generation services with guaranteed user privacy protection.

In this paper, we consider a new design of synchronous motor with salient poles rotor and all coils placed on the stator. This design, uses a laminated silicon steel rotor, which is not so expensive as a rotor with super strong permanent magnets. This design of machine eliminates copper rings on the rotor and brushes which is used in regular synchronous motors, and eliminates disadvantages involved with these arrangements. In an earlier publication, authors considered the opportunity realization of synchronous mode operation in the machine with salient pole rotor and DC stator excitation. Now, we consider the new synchronous mode operation with individual DC excitation of each the alternative current (AC) windings for realization the first, second and third phase synchronous machines. In theoretical basics of analyses and design of synchronous motors we pay more attention to the single-phase motor because it is the basis for design polyphase synchronous machines.

Charge boosting strategy plays an essential role in improving the power density of diesel engines while meeting stringent emissions regulations. In downsized two-stage turbocharged engines, turbocharger matching is critical to achieve desired boost pressure while maintaining sufficiently fast transient response. A numerical simulation model is developed to evaluate the effect of two-stage turbocharger configurations on the perceived vehicle acceleration. The simulation model developed in GT-SUITE consists of engine, drivetrain, and vehicle dynamics sub-models. A model-based turbocharger control logic is developed in MATLAB using an analytical compressor model and a mean-value engine model. The components of the two-stage turbocharging system evaluated in this study include a variable geometry turbine in the high-pressure stage, a compressor bypass valve in the low-pressure stage and an electrically assisted turbocharger in the low-pressure stage.

This paper begins with a baseline multi-objective optimization problem for the lithium-ion battery cell. Maximizing the energy per unit separator area and minimizing the mass per unit separator area are considered as the objectives when the thickness and the porosity of the positive electrode are chosen as design variables in the baseline problem. By employing a reaction zone model of a Graphite/Iron Phosphate Lithium-ion Cell and the Genetic Algorithm, it is shown the shape of the Pareto optimal front for the formulated optimization takes a convex form. The identified shape of the Pareto optimal front is expected to guide Design of Experiments (DOE) and product design. Compared with the conventional studies whose optimizations are based on a single objective of maximizing the specific energy, the proposed multi-objective optimization approach offers more flexibility to the product designers when trade-off between conflicting objectives is required.

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway).

This study considers the thermal stresses in single lap adhesive joints between magnesium and steel. The source of thermal stresses is the large difference in the coefficients of thermal expansion of magnesium and steel. Two different temperature differentials from the ambient conditions (23°C) were considered, namely -30°C and +50°C. Thermal stresses were determined using finite element analysis. In addition to Mg-steel substrate combination, Mg-Mg and steel-steel combinations were also studied. Combined effect of temperature variation and applied load was also explored. It was observed that temperature increase or decrease can cause significant thermal stresses in the adhesive layer and thermal stress distribution in the adhesive layer depends on the substrate combination and the applied load.

In the North American automotive industry, various advanced high strength steels (AHSS) are used to lighten vehicle structures, improve safety performance and fuel economy, and reduce harmful emissions. Relatively thick gages of AHSS are commonly joined to conventional high strength steels and/or mild steels using Gas Metal Arc Welding (GMAW) in the current generation body-in-white structures. Additionally, fatigue failures are most likely to occur at joints subjected to a variety of different loadings. It is therefore critical that automotive engineers need to understand the fatigue characteristics of welded joints. The Sheet Steel Fatigue Committee of the Auto/Steel Partnership (A/S-P) completed a comprehensive fatigue study on GMAW joints of both AHSS and conventional sheet steels including: DP590 GA, SAE 1008, HSLA HR 420, DP 600 HR, Boron, DQSK, TRIP 780 GI, and DP780 GI steels.

This paper describes the design and application of a business simulation to help train employees about the new business model and culture that for an automotive supplier company that designs connected vehicle and other advanced electronic products for the automotive industry. The simulation, called SIM-i-TRI, is a three to four day collaborative learning activity that simulates the executive, administrative, engineering, manufacturing, and marketing functions in three divisions of a manufacturer that supplies parts and systems to customers in industries similar to the automotive industry. It was originally designed to support the new employee orientation at the Tier 1 supplier and to provide the participants a safe environment to practice the lessons from the orientation. The simulation has been used several times a month in the US, England, and Germany for over four years.

The automotive industry is expected to accelerate the transition to revolutionary products, rapid changes in technology and increasing technological sophistication. This will require engineers to advance their knowledge, connect and integrate different areas of knowledge and be skilled in synthesis. In addition, they must learn to work in cross-disciplinary teams and adopt a systems approach. The College of Engineering and Computer Science (CECS) at the University of Michigan-Dearborn (UM-Dearborn) responded by creating interdisciplinary MS and Ph.D. programs in automotive systems engineering (ASE) and augmenting them with hands-on research. Students at the undergraduate level can also engage in numerous ASE activities. UM-Dearborn's ASE programs offer interesting and possibly unique advantages. The first is that it offers a spectrum of ASE degree and credit programs, from the MS to the Ph.D. to continuing education.