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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.

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.

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.

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.

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.

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.

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.

This study investigated the effects of three navigation system human-machine interfaces (HMIs) on driver eye-glance behavior, navigational errors, and subjective assessments. Thirty-six drivers drove an unfamiliar 3-segment route in downtown Detroit. HMIs were 2D or 3D (level-of-detail) electronic map display + standard voice prompts, or 3D map-display augmented by photorealistic images + landmark-enhanced voice prompts. Participants drove the same three route segments in order but were assigned a different HMI condition/segment in a 3-period/3-treatment crossover experimental design. Results indicate that drivers’ visual attention using the advanced navigation systems HMIs were within US Department of Transportation recommended visual distraction limits. More turns missed in the first route segment, regardless of HMI, were attributable to greater route complexity and a late-onset voice prompt. Participant’s ratings of HMIs were influenced by the context in which that HMI was used.

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.

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).

We present research in progress to develop and implement a transportable instrumentation package (TIP) to collect driver data in a vehicle. The overall objective of the project is to investigate the symbiotic relationship between humans and their vehicles. We first describe the state-of-art technologies to build the components of TIP that meet the criteria of ease of installation, minimal interference with driving, and sufficient signals to monitor driver state and condition. This method is a viable alternative to current practice which is to first develop a fully instrumented test vehicle, often at great expense, and use it to collect data from each participant as he/she drives a prescribed route. Another practice, as for example currently being used in the SHRP-2 naturalistic driving study, is to install the appropriate instrumentation for data collection in each individual's vehicle, often requiring several hours.

This paper presents results of a three-phase research project aimed at understanding how future automotive interior materials should be selected or designed to satisfy the needs of the customers. The first project phase involved development of 22 five-point semantic differential scales to measure visual, visual-tactile, and evaluative characteristics of the materials. Some examples of the adjective pairs used to create the semantic differential scales to measure the perceptual characteristics of the material are: a) Visual: Light vs. Dark, Flat vs. Shiny, etc., b) Visual-Tactile: Smooth vs. Rough, Slippery vs. Sticky, Compressive vs. Non-Compressive, Textured vs. Non-Textured, etc., c) Evaluative (overall perception): Dislike vs. Like, Fake vs. Genuine, Cheap vs. Expensive, etc. In the second phase, 12 younger and 12 older drivers were asked to evaluate a number of different automotive interior materials by using the 22 semantic differential scales.

Fuel cell based powertrains are considered as potential candidates for future vehicles. Modeling of vehicle powertrains, using a combination of components and energy storage media, are widely used to predict vehicle performances under different duty cycles. This paper deals with performance analysis of a light-duty vehicle comprised of a PEM fuel cell stack, in combination with different energy storage systems using Powertrain Simulation Analysis Toolkit (PSAT). The performance of the stack was characterized by experimental data on a smaller PEM stack and was used in the simulation. The stack data was collected at controlled loading and thermal parameters. Three energy storage systems are considered in the analysis: nickel metal hydride battery storage, lithium-ion battery storage and ultra capacitor energy storage. The simulation results were analyzed for comparative evaluations and to optimize the performance of the fuel cell powertrain configurations.

The urban trams with a low floor are more convenient for the passengers, and with a high floor - more cheaply and more technologically during manufacturing and operation. The combined advantages those and others in themselves are trams with average height of a floor, but for this purpose it is necessary to lower height of tram carriages, that is reached by application of electric motors with a small stator external diameter. It is offered in this the perspective electric drive on the base of the synchronous motor with independent excitation. The salient rotor poles of the motor do not contain windings. The motors stator is carried out on the base of the stator body of regular AC electric motor. The multiphase winding is located in the stator. A winding section, which conductors settle down above the between rotor poles, carry out a role of the excitation winding, and others, which conductors lay above poles, - a role of the armature winding.

This paper presents results of a study conducted to compare driving behavior and performance of drivers in two different fixed-base driving simulators (namely, FAAC and STI) while performing a same set of distracting tasks under geometrically similar freeway and traffic conditions. The FAAC simulator had a wider three-screen road view with steering feedback as compared to the STI simulator which had a single screen and narrower road view and had no steering feedback. Twenty four subjects (12 younger and 12 mature) drove each simulator and were asked to perform a set of nine different tasks involving different distracting elements such as, using a cell phone, operating the car radio, retrieving and selecting a map from map pocket in the driver's door, collecting coins to pay toll, etc.

Security is a huge concern in VANETs (Vehicular Ad hoc NETworks) since the information being conveyed may affect life-or-death decisions. One of the security concerns is the Sybil Attack. This attack attempts to create multiple identities to disrupt or control the network. A malicious node utilizing the Sybil Attack in VANETs can disrupt the network in various ways. It can create a large number of Sybil nodes to intervene in message forwarding, potentially causing a massive pileup and great loss of life. A malicious node can also use the Sybil Attack to create illusions of traffic congestions, getting other drivers to take alternate routes and leaving a clear path for the malicious node to its destination. In this paper, we discuss several defense strategies for the Sybil Attack in VANETs.

This paper presents quantitative effects of windshield veiling glare on the visibility of targets based on a two part research project. The first part involved measurement and modeling of luminance of veiling glare caused by the reflection of different instrument panel materials under range of conditions defined by combination of windshield angle, instrument panel angle, and sun angle. In the second part, the veiling glare model was incorporated in a visibility prediction model based on visual contrast threshold data. A critical visibility condition of a driver approaching a tunnel with the sunlight falling on his windshield and attempting to detect a target inside the tunnel was studied by conducting sensitivity analyses. The sensitivity analysis showed that a 2 ft diameter 10% reflectance target illuminated by 5000 lux of lighting inside a tunnel visibility distances can be seen from 0 to 3,000 feet depending upon driver's age, vehicle design parameters and sun illumination levels.