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The paper solves the problem of increasing the accuracy of measuring torque and use of an electronic torque meter as a feedback sensor of synchronous and induction machines of an electric traction drive. Relevance of the problem and methods for its solving by indirect means using simulation models of electric machines are considered. The theoretical development of the meter is based on the energy model of electric machines in the form of differential equations for active and reactive power balance. This eliminates the direct influence of instability and nonlinearity of inductive elements and takes into account electrical, magnetic, mechanical, and harmonic losses using the simplest algorithms. Key variables of the model in the form of total active power and angular velocity are measured directly, and the high nominal efficiency of traction machines (95%) provides a wide tolerance range for calculating total losses.

Owing to their weight saving potential and improved flexural stiffness, metal-polymer-metal sandwich laminates are finding increasing applications in recent years. Increased use of such laminates for automotive body panels and structures requires not only a better understanding of their mechanical behavior, but also their formability characteristics. This study focuses on the formability of a metal–polymer-metal sandwich laminate that consists of AA5182 aluminum alloy as the outer skin layers and polypropylene (PP) as the inner core. The forming limit curves of Al/PP/Al sandwich laminates are determined using finite element simulations of Nakazima test specimens. The numerical model is validated by comparing the simulated results with published experimental results. Strain paths for different specimen widths are recorded.

Controller Area Network (CAN), the de facto standard for in-vehicle networks, has insufficient security features and thus is inherently vulnerable to various attacks. To protect CAN bus from attacks, intrusion detection systems (IDSs) based on advanced deep learning methods, such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN), have been proposed to detect intrusions. However, those models generally introduce high latency, require considerable memory space, and often result in high energy consumption. To accelerate intrusion detection and also reduce memory requests, we exploit the use of Binarized Neural Network (BNN) and hardware-based acceleration for intrusion detection in in-vehicle networks. As BNN uses binary values for activations and weights rather than full precision values, it usually results in faster computation, smaller memory cost, and lower energy consumption than full precision models.

Tubular sections are found in many automotive structural components such as front rails, cross beams, and sub-frames. They are also used in other vehicular structures, such as buses and rails. In many of these components, smaller tubular sections may be joined together using an adhesive to build the required structure. For crash safety applications, it is important that the joined tube sections be able to provide high energy absorption capability and withstand the impact load before the adhesive bond failure occurs. In this study, single lap tubular joints between two aluminum tubes are investigated for their crush performance at both quasi-static and high impact speeds using finite element analysis. A crash optimized adhesive Betamate 1496 is considered. The joint parameters, such as adhesive overlap length, tube diameters and tube lengths, are varied to determine their effects on energy absorption, peak and mean loads, and tube deformation mode.

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 new wireless rotor electrical machine has all the coils placed on the stator. The laminated wireless rotor serves as a magnetic field switcher. A wireless rotor is cold, and it facilitates machine cooling. The model of the wireless rotor machine includes electrical and mechanical components. The wireless rotor machines can find an application in practice because they have advantages over existing devices. In modeling, we use a new approach. We consider a motor as a natural control system with torque feedback. Such an approach simplifies analyses and adjustment of the operation of an electrical machine. First, we analyze an open-loop control system without torque feedback. In this case, by changing the rotor speed under external torque, we can receive the torque-speed motor characteristics. After some adjustments to the open-loop system, we can consider the close loop control system with torque feedback. We use a space vector representation for sinusoidal electric components.

The engine operating point (EOP), which is determined by the engine speed and torque, is an important part of a vehicle's powertrain performance and it impacts FC, available propulsion power, and emissions. Predicting instantaneous EOP in real-time subject to dynamic driver behaviour and environmental conditions is a challenging problem, and in existing literature, engine performance is predicted based on internal powertrain parameters. However, a driver cannot directly influence these internal parameters in real-time and can only accommodate changes in driving behaviour and cabin temperature. It would be beneficial to develop a direct relationship between the vehicle-level parameters that a driver could influence in real-time, and the instantaneous EOP. Such a relationship can be exploited to dynamically optimize engine performance.

The diesel engine with direct injection of hydrogen gas has clear advantages over the hydrogen engine with forced ignition of a hydrogen-air mixture. Despite of this, the concept of hydrogen-diesel engine has not investigated until now. In the paper, a detailed study of the working process of hydrogen-diesel engine carried out for the first time. Based on the results of the experimental studies and mathematical modeling, it has established that the behavior of thermo-physical processes in the combustion chamber of hydrogen-diesel engine, in a number of cases, differs fundamentally from the processes that take place in the conventional diesel engines. There have been identified the reasons for their difference and determined the values of the operating cycle parameters of hydrogen diesel engine, which provide the optimal correlation between the indicator values and the environmental performance.

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.

Regular induction motors operate at a constant value of voltage. They operate from zero external load to rated value. At low loads, motors works with reserve of the power. At low loads, motor can work with lower voltage, with lower current (lower power losses) and higher power factor (cos φ). In the paper, we consider theoretical basics of reduction of idle current and increase power factor in idle mode operation. We consider speed controller by changing value of motor voltage. With this controller, we can reduce idle current and increase its power factor. In addition, we consider current controller for limiting starting current by decreasing voltage during motor start, and reduction idle current with improved power factor in idle steady state conditions. Voltage change includes controlled (thyristor) rectifier or pulse width modulated converter of voltage. Controllers can include speed or current feedbacks. We consider digital model of induction motor with different controllers.

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.

Warpage is the distortion induced by inhomogeneous shrinkage during injection molding of plastic parts. Uncontrolled warpage will result in dimensional instability and bring a lot of challenges to the mold design and part assembly. Current commercial simulation software for injection molding cannot provide consistently accurate warpage prediction, especially for semi-crystalline thermoplastics. In this study, the root cause of inconsistency in warpage prediction has been investigated by using injection molded polypropylene plaques with a wide range of process conditions. The warpage of injection molded plaques are measured and compared to the numerical predictions from Moldex3D. The study shows that with considering cooling rate effect on crystallization kinetics and using of the improved material model for residual stress calculations, good agreements are obtained between experiment and simulation results.

The problem of increasing the accuracy of determining the torque and the load angle of the permanent magnet synchronous motor of an electric traction drive to the predicted level (2.5...3)% of the full-scale error is solved by an indirect method. We considered the algorithms for calculating the generalized current and voltage of the electric motor, the total power, the instantaneous values of the power factor, and the sine of the phase angle between the first harmonics of voltages and currents. We determined the requirements for the accuracy of determining these values at the level of 1% of the full-scale error. We considered the algorithms for determining the total instantaneous power losses by the indirect method at the predicted level (15...20)% of the full-scale error with the efficiency of the motor (90...95)%.

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.

Over the decades, several attempts have been made to develop new fatigue analysis methods for welded joints since most of the incidents in automotive structures are joints related. Therefore, a reliable and effective fatigue damage parameter is needed to properly predict the failure location and fatigue life of these welded structures to reduce the hardware testing, time, and the associated cost. The nodal force-based structural stress approach is becoming widely used in fatigue life assessment of welded structures. In this paper, a new nodal force-based structural stress recovery procedure is proposed that uses the least squares method to linearly smooth the stresses in elements along the weld line. Weight function is introduced to give flexibility in choosing different weighting schemes between elements. Two typical weighting schemes are discussed and compared.