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This paper presents the extended Kalman filter-based sideslip angle estimator design using a nonlinear 5DoF single-track vehicle dynamics model with stochastic modeling of tire forces. Lumped front and rear tire forces have been modeled as first-order random walk state variables. The proposed estimator is primarily designed for vehicle sideslip angle estimation; however it can also be used for estimation of tire forces and cornering stiffness. This estimator design does not rely on linearization of the tire force characteristics, it is robust against the variations of the tire parameters, and does not require the information on coefficient of friction. The estimator performance has been first analyzed by means of computer simulations using the 10DoF two-track vehicle dynamics model and underlying magic formula tire model, and then experimentally validated by using data sets recorded on a test vehicle.

The use of electric motors to independently control the torque of two or four wheels of a vehicle has the potential to significantly improve safety and handling. One virtue of electric motors is that their output torque can be accurately estimated. Using this known output torque, longitudinal tire force and coefficient of friction can be estimated via a controller output observer. This observer works by constructing a model of wheel dynamics, with longitudinal tire force as an unknown input quantity. A known wheel torque is input to the physical and modeled system and the resulting measured and predicted wheel speeds are compared. The error between the measured and predicted wheel speed is driven towards zero by a robust feedback controller. This controller modulates an estimate of longitudinal tire force used as an input by the wheel dynamics model. The resulting estimate of longitudinal tire force quickly converges towards the actual value with minimal computational expense.

Pre-collision systems (PCS) use forward-looking sensors to detect the location and motion of vehicles ahead and provide a sequence of actions to help the driver either avoid striking the rear-end of another vehicle or mitigate the severity of the crash. The actions include driver alerts, amplification of driver braking as distance decreases (dynamic brake support, DBS), and automatic braking if the driver has not acted or has not acted sufficiently (crash imminent braking, CIB). Recent efforts by various organizations have sought to define PCS objective test procedures and test equipment in support of consumer information programs and potential certification. This paper presents results and insights from conducting DBS and CIB tests on two production vehicles sold in the US. Eleven scenarios are used to assess the systems' performance. The two systems' performance shows that commercial systems can be quite different.

In some automotive electrical systems, it is advantageous to use power supplies and loads at two or more voltages. Often it is desirable to retain the single wire power architecture, with the car body providing the return circuit. A major difficulty in achieving this end is the matter of dealing with the possibility of a short circuit between feed wires at different voltages. It can be shown that source-side fuses cannot be relied upon to return the system to a safe state in all cases. Substantial effort was applied to this problem in the early years of the 21st century, but the results were less than completely satisfactory. Using entirely separate cable harnesses for each voltage, with physically separated routing, minimizes the risk of such a short occurring in the harness.

Advanced driver assistance systems like cooperative adaptive cruise control (CACC) are designed to exploit information provided by vehicle-to-vehicle (V2V) and/or infrastructure-to-vehicle (I2V) communication systems to achieve desired objectives such as safety, traffic fluidity or fuel economy. In a day to day traffic scenario, the presence of unknown disturbances complicates achieving these objectives. In particular, CACC benefits in terms of fuel economy require the prediction of the behavior of a preceding vehicle during a finite time horizon. This paper suggests an estimation method based on actual and past inter-vehicle distance data as well as on traffic and upcoming traffic lights. This information is used to train a set of nonlinear, autoregressive (NARX) models. Two scenarios are investigated, one of them assumes a V2V communication with the predecessor, the other uses only data acquired by on-board vehicle sensors.

Towards developing of advanced driver specific active/passive safety systems it is important to be able to continuously evaluate driving performance variations. These variations are best captured when evaluated against similar driving patterns or maneuvers. Hence, accurate maneuver recognition in the preliminary stage is vital for the evaluation of driving performance. Rather than using simulated or fixed test track data, it is important to collect and analyze on-road real-traffic naturalistic driving data to account for all possible driving variations in different maneuvers. Towards this, massive free style naturalistic driving data corpora are being collected. Human transcription of these massive corpora is not only a tedious task, but also subjective and hence prone to errors/inconsistencies which can be due to multiple transcribers as well as lack of enough training/instructions.

The last years have seen an increasing amount of innovations in the functionality of car electronics (e.g. advanced driver assistant systems (ADAS) and in-vehicle infotainment systems (IVIS)). These electrical systems are not reserved for premium cars anymore, but additionally reach mid-size, compact, and subcompact cars. The growing number of functionalities in these cars entails increasing amount of interfaces, which may confuse, overload, or annoy the driver. Accompanying this, there is a trend towards the integration of capacitive touchscreens as user interfaces. These touchscreens were implemented first in consumer electronics and had a substantial impact on the way in which users interact with technology. This in turn has led to an increased user driven demand for the technology to be implemented in other domains, even in safety-critical ones like the automotive area.

Proper operation of an internal combustion engine is required by demands of a vehicle driver and governmental legislations. Therefore it is necessary to monitor, within an online technique, the engine and detect any fault which disrupts its normal operation. In this paper, the air-charge path, as a key element in a turbocharged engine, is monitored for an air leakage fault. At first, a robust algorithm to estimate unmeasured turbocharger rotational speed is presented. The sliding mode methodology is used to design the estimator which is shown to be robust to the compressor modeling uncertainties. The estimation error from the sliding mode observer (SMO) is then used to detect abnormal behavior of the turbocharger along with the engine due to a leakage fault in the air-charge path. Experimental results from a modern turbocharged SI engine indicate the designed monitoring technique is able to detect a leakage fault, of 7 mm or higher sizes, in the air-charge path.

In this paper, we propose algorithms for cost minimization of physical wires that are used to connect electronic devices in the vehicle. The wiring cost is one of the most important drivers of electrical architecture selection. Our algorithms perform wire routing from a source device to a destination device through harnesses, by selecting the optimized wire size. In addition, we provide optimized splice allocation with limited constraints. Based on the algorithms, we develop a tool which is integrated into an off-the-shelf optimization and workflow system-level design tool. The algorithms and the tool provide an efficient, flexible, scalable, and maintainable approach for cost analysis and architecture selection.

This paper presents the most recent advancement in the vehicle development process using the one-step or auto Transfer Path Analysis (TPA) in conjunction with the superelement, component mode synthesis, and automated multi-level substructuring techniques. The goal is to identify the possible ways of energy transfer from the various sources of excitation through numerous interfaces to given target locations. The full vehicle model, consists of superelements, has been validated with the detailed system model for all loadcases. The forces/loads can be from rotating components, powertrain, transfer case, chain drives, pumps, prop-shaft, differential, tire-wheel unbalance, road input, etc., and the receiver can be at driver/passenger ears, steering column/wheel, seats, etc. The traditional TPA involves two solver runs, and can be fairly complex to setup in order to ensure that the results from the two runs are consistent with subcases properly labeled as input to the TPA utility.

This paper includes analysis results for the control strategy of the Peugeot 3008 Hybrid4, a diesel-electric hybrid vehicle, under different thermal conditions. The analysis was based on testing results obtained under the different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory (ANL). The objectives were to determine the principal concepts of the control strategy for the vehicle at a supervisory level, and to understand the overall system behavior based on the concepts. Control principles for complex systems are generally designed to maximize the performance, and it is a serious challenge to determine these principles without detailed information about the systems. By analyzing the test results obtained in various driving conditions with the Peugeot 3008 Hybrid4, we tried to figure out the supervisory control strategy.

In order to determine the overall fuel economy of a plug-in hybrid electric vehicle (PHEV), the amount of operation in charge depleting (CD) versus charge sustaining modes must be determined. Mode of operation is predominantly dependent on customer usage of the vehicle and is therefore highly variable. The utility factor (UF) concept was developed to quantify the distance a group of vehicles has traveled or may travel in CD mode. SAE J2841 presents a UF calculation method based on data collected from travel surveys of conventional vehicles. UF estimates have been used in a variety of areas, including the calculation of window sticker fuel economy, policy decisions, and vehicle design determination. The EV Project, a plug-in electric vehicle charging infrastructure demonstration being conducted across the United States, provides the opportunity to determine the real-world UF of a large group of privately owned Chevrolet Volt extended range electric vehicles.

The switched reluctance motor (SRM) driver is receiving increasing attention from various researchers as well as industry as a viable for adjustable speed and servo applications. Combining the unique features of an SRM with simple and efficient power converter that in use, a superior motor drive system emerges which may be preferable for many applications compared to other AC or DC motor driver systems. Although a number of converters have emerged over the years for SRM drives, but every single driver has its own advantages and drawbacks and there has always been a trade-off between gaining something of the advantages and losing some when a new driver is offered.

The noise radiated by an electrical motor is very different from the one generated by an internal combustion engine. It is characterized by the emergence of high frequency pure tones that can be annoying and badly perceived by future drivers, even if the overall noise level is lower than that of a combustion engine. A simulation methodology has been proposed, consisting in a multi-physical approach to simulate the dynamic forces and noise radiated by electric motors. The principle is first to calculate the excitation due to electromagnetic phenomena (Maxwell forces) using an electromagnetic finite element solver. This excitation is then projected onto the structure mesh of the stator in order to calculate the dynamic response. Finally, the radiated sound power is calculated with the aid of a standard acoustic finite element method. The calculation methodology assumes a weak coupling between the different physical levels. It has been validated by comparison with the experiment.

The driving comfort is an important factor for buying decisions. Especially for battery electric vehicles (BEV) the acoustic quality is an elementary distinguishing feature, since the masking of an internal combustion engine (ICE) is no longer present. Opposing the importance of the acoustic quality is the lack of knowledge of how to measure and interpret the high frequency noise generated by an electric powertrain with respect to the NVH behavior influencing the passengers [1, 2]. In this contribution a method for measuring and interpreting the transfer path of acoustic phenomena from the drivetrain of a battery electric vehicle into the passenger cabin is presented. Due to the lack of masking by the ICE in case of BEV, high frequency phenomena must be considered as well. In order to determine the airborne transfer function from the electric powertrain to the driver cabin, a dodecahedral speaker is used for reciprocal measurements.

Low interior noise levels in combination with a comfortable sound is an important task for passenger cars. Due to the reduction of many noise sources over the last decades, nowadays tire-road noise has become one of the dominant sources for the interior noise. Especially for manufactures of luxury cars, the reduction of tire-road noise is a big challenge and therefore a central part of NVH development. The knowledge of the noise transmission behavior based on the characteristics of the relevant sources is a fundamental of a modern NVH - development process. For tire-road noise the source characteristics can be described by wheel forces and radiated airborne noise. In combination with the related vehicle transfer functions it is possible to describe the noise transmission behavior in detail. A method for estimating wheel forces and radiated airborne noise is presented.

This study was designed to investigate how the spectral power distribution (SPD) of LED headlamps (including correlated color temperature, CCT) affects both objective driving performance and subjective responses of drivers. The results of this study are not intended to be the only considerations used in choosing SPD, but rather to be used along with results on how SPD affects other considerations, including visibility and glare. Twenty-five subjects each drove 5 different headlamps on each of 5 experimental vehicles. Subjects included both males and females, in older (64 to 85) and younger (20 to 32) groups. The 5 headlamps included current tungsten-halogen (TH) and high-intensity discharge (HID) lamps, along with three experimental LED lamps, with CCTs of approximately 4500, 5500, and 6500 K. Driving was done at night on public roads, over a 21.5-km route that was selected to include a variety of road types.

When employing in-car active sound generation (ASG) and active noise cancellation (ANC), the accurate knowledge of the vehicle interior sound pressure distribution in magnitude as well as phase is paramount. Revisiting the ANC concept, relevant boundary conditions in spatial sound fields will be addressed. Moreover, within this study the controllability and observability requirements in case of ASG and ANC were examined in detail. This investigation focuses on sound pressure measurements using a 24 channel microphone array at different heights near the head of the driver. A shaker at the firewall and four loudspeakers of an ordinary in-car sound system have been investigated in order to compare their sound fields. Measurements have been done for different numbers of passengers, with and without a dummy head and real person on the driver seat. Transfer functions have been determined with a log-swept sine technique.

An understanding of the flow around a tire in contact with the ground is important when designing fuel-efficient tires as the aerodynamic drag accounts for about one third of an entire vehicle's rolling loss. Recently, non-pneumatic tires (NPTs) have drawn attention mainly due to their low rolling resistance associated with the use of low viscoelastic materials in their construction. However, an NPT's fuel efficiency should be re-evaluated in terms of aerodynamic drag: discrete flexible spokes in an NPT may cause more aerodynamic drag, resulting in greater rolling resistance. In this study, the aerodynamic flow around a non-pneumatic tire in contact with the ground is investigated for i) stationary and ii) rotating cases using the steady state Reynolds-Averaged Navier-Stokes (RANS) method. A sensitivity analysis was carried out with a varying mesh density. The flow into cavity by the discrete spoke geometry of the NPT does not significantly affect the overall aerodynamic drag.

The number of elderly drivers is increasing in Japan and ensuring the safety of elderly drivers is becoming an important issue. The authors previously conducted an analysis of the characteristics of accidents and traffic violations by elderly drivers based on the number of accidents in which they were rear-ended. This method was used in order to exclude the influence of driving frequency. As a result of that analysis, it was found that the likelihood of violations committed by elderly drivers was not particularly higher than in other age groups, while the likelihood of accidents caused by them was higher. The risk of causing an accident was judged to be about two times higher in elderly drivers than in the 35-44 year age group. However, the methodology presupposed that collisions in which a driver is rear-ended are accidents that occur randomly, and that they occur with the same probability in each age group.