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Driver assistance systems (e.g. the emergency brake assist Active Brake Assist2, or ABA2 for short, in the Mercedes-Benz Actros) are becoming increasingly common in heavy-duty commercial vehicles. Due to the close interconnection with drivetrain and suspension control systems, the integration and validation of the functions make the most exacting demands on processes and tools involved in mechatronics development. Presenter Thomas Bardelang, Daimler AG

The BMW Group has introduced electric cars to the market with the MINI E already in 2009. The next step will be the launch of the BMW ActiveE in 2011, followed by the revolutionary Mega City Vehicle in 2013. The presentation will explain the BMW Group strategy for implementing sustainable mobility. A focus will be emobility, the use of carbon fiber and the holistic sustainability approach of BMW Group?s project i. Reference will be made to the research results of the MINI E projects in the US and in Europe. Presenter Andreas Klugescheid, BMW AG

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.

In an effort to characterize the dynamics typical of school bus operation, National Renewable Energy Laboratory (NREL) researchers set out to gather in-use duty cycle data from school bus fleets operating across the country. Employing a combination of Isaac Instruments GPS/CAN data loggers in conjunction with existing onboard telemetric systems resulted in the capture of operating information for more than 200 individual vehicles in three geographically unique domestic locations. In total, over 1,500 individual operational route shifts from Washington, New York, and Colorado were collected. Upon completing the collection of in-use field data using either NREL-installed data acquisition devices or existing onboard telemetry systems, large-scale duty-cycle statistical analyses were performed to examine underlying vehicle dynamics trends within the data and to explore vehicle operation variations between fleet locations.

Battery electric vehicles possess great potential for decreasing lifecycle costs in medium-duty applications, a market segment currently dominated by internal combustion technology. Characterized by frequent repetition of similar routes and daily return to a central depot, medium-duty vocations are well positioned to leverage the low operating costs of battery electric vehicles. Unfortunately, the range limitation of commercially available battery electric vehicles acts as a barrier to widespread adoption. This paper describes the National Renewable Energy Laboratory's collaboration with the U.S. Department of Energy and industry partners to analyze the use of small hydrogen fuel-cell stacks to extend the range of battery electric vehicles as a means of improving utility, and presumably, increasing market adoption.

This paper describes the possibility to resolve aeroacoustic feedback with a commercial 2nd/3rd order finite volume CFD code [1]. After a first comparison to a NACA 0012 test case, tonal noise components of a realistic automotive side view mirror are validated with in-house wind tunnel measurements. A zonal RANS/LES approach is used to ensure a realistic flow around the exterior side mirror mounted on a Mercedes-Benz passenger car. The provided compressible large eddy simulations are using non-reflecting boundary conditions in combination with a sponge zone approach to reduce hydrodynamic fluctuations and are in great accordance to measurements. The possibility of localizing and investigating the underlying feedback mechanism enables the chance for a targeted design of different appropriate remedies, which are finally confirmed by means of experimental comparison.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

We investigate tradeoffs between the airflow strategies related to engine cooling and the aerodynamic-enabled fuel savings created by platooning. By analyzing air temperatures, engine temperatures and cooling air flow at different platoon distances, we show the thermal impact to the engine from truck platooning. Previously, we collected wind and thermal data for numerous heavy-duty truck platoon configurations (gaps ranging from 4 to 87 meters) and reported the significant fuel savings enabled by these configurations. The fuel consumption for all trucks in the platoon were measured using the SAE J1321 gravimetric procedure as well as calibrated J1939 instantaneous fuel rate while travelling at 65 mph and loaded to a gross weight of 65,000 lb.

The reliability of electronic components is of increasing importance for further progress towards automated driving. Thermal aging processes such as electromigration is one factor that can negatively affect the reliability of electronics. The resulting failures depend on the thermal load of the components within the vehicle lifetime - called temperature collective - which is described by the temperature frequency distribution of the components. At present, endurance testing data are used to examine the temperature collective for electronic components in the late development stage. The use of numerical simulation tools within Vehicle Thermal Management (VTM) enables lifetime thermal prediction in the early development stage, but also represents challenges for the current VTM processes [1, 2]. Due to the changing focus from the underhood to numerous electronic compartments in vehicles, the number of simulation models has steadily increased.

Electric drive vehicles (EDVs) have complex thermal management requirements not present in conventional vehicles. In addition to cabin conditioning, the energy storage system (ESS) and power electronics and electric motor (PEEM) subsystems also require thermal management. Many current-generation EDVs utilize separate cooling systems, adding both weight and volume, and lack abundant waste heat from an engine for cabin heating. Some use battery energy to heat the cabin via electrical resistance heating, which can result in vehicle range reductions of 50% under cold ambient conditions. These thermal challenges present an opportunity for integrated vehicle thermal management technologies that reduce weight and volume and increase cabin heating efficiency. Bench testing was conducted to evaluate a combined fluid loop technology that unifies the cabin air-conditioning and heating, ESS thermal management, and PEEM cooling into a single liquid coolant-based system.

With the reduction of engine and road noise, wind has become an important source of interior noise when cruising at highway speed. The challenges of weight reduction, performance improvement and reduced development time call for stronger support of the development process by numerical methods. Computational Fluid Dynamics (CFD) and finite element (FE) vibroacoustic computations have reached a level of maturity that makes it possible and meaningful to combine these methods for wind noise prediction. This paper presents a method used for coupling time domain CFD computations with a finite element vibroacoustic model of a vehicle for the prediction of low-frequency wind noise below 500 Hz. The procedure is based on time segmentation of the excitation load and transformation into the frequency domain for the vibroacoustic computations. It requires simple signal processing and preserves the random character as well as the spatial correlation of the excitation signal.

Aero-vibro-acoustic prediction of interior noise associated with exterior flow requires accurate predictions of both fluctuating surface pressures across the exterior of a vehicle and efficient models of the vibro-acoustic transmission of these surface pressures to the interior of a vehicle. The simulation strategy used in this paper combines both CFD and vibro-acoustic methods. An accurate excitation field (which accounts for both hydrodynamic and acoustic pressure fluctuations) is calculated with a hybrid CAA approach based on an incompressible unsteady flow field with an additional acoustic wave equation. To obtain the interior noise level at the driver's ears a vibro-acoustic model is used to calculate the response of the structure and interior cavities. The aero-vibro-acoustic simulation strategy is demonstrated for a Mercedes-Benz S-class and the predictions are compared to experimental wind tunnel measurements.

The driving comfort is an important factor for buying decisions. For the interior noise of battery electric vehicles (BEV) high frequency tonal orders are characteristic. They can for example be caused by the gearbox or the electric drive and strongly influence the perception and rating of the interior noise by the customer. In this contribution methods for measuring, analyzing and predicting the excitation by the dynamic torque of the electric drive are presented. The dynamic torque of the electric drive up to 3.5 kHz is measured on a component test bench with the help of high frequency, high precision torque transducer. The analysis of the results for the order of interest shows a good correlation with the acoustic measurements inside the corresponding vehicle. In addition an experimental and numerical modal analysis of the rotor of the electric drive are performed.

Battery second use-putting used plug-in electric vehicle (PEV) batteries into secondary service following their automotive tenure-has been proposed as a means to decrease the cost of PEVs while providing low cost energy storage to other fields (e.g., electric utility markets). To understand the value of used automotive batteries, however, we must first answer several key questions related to battery degradation, including: How long will PEV batteries last in automotive service? How healthy will PEV batteries be when they leave automotive service? How long will retired PEV batteries last in second-use service? How well can we best predict the second-use lifetime of a used automotive battery? Under the support of the U.S. Department of Energy's Vehicle Technologies Office, the National Renewable Energy Laboratory has developed a methodology and the requisite tools to answer these questions, including the Battery Lifetime Simulation Tool (BLAST).

Connectivity has become an essential need for daily device users. With the car projected to be the “ultimate mobile device”, connectivity modules will eventually be mainstream in every car. Network providers are expanding their infrastructure and technology to accommodate the connected cars. Besides making voice and emergency calls the connected car will be sharing data with telematics service providers, back end systems and other vehicles. This trend will increase vehicle modules, complexity, entry points and vulnerabilities. This paper will present the current connected car architectures. The paper will present current architectural issues of the connected car and its vulnerabilities. The paper will present a new proposed architecture for the future connected car that enhances efficiency and security.

Prediction of flow induced noise in the interior of a passenger car requires accurate representations of both fluctuating surface pressures across the exterior of the vehicle and efficient models of the vibro-acoustic transmission of these surface pressures to the driver’s ear. In this paper, aeroacoustic and vibro-acoustic methods are combined in order to perform an aero-vibro-acoustic analysis of a Mercedes-Benz A-class. The exterior aero-acoustic method consists of a time domain incompressible Detached Eddy Simulation (DES) and an acoustic wave equation. The method is extended in this paper to account for convection effects when modelling the exterior sound propagation. The interior vibro-acoustic model consists of a frequency domain Finite Element (FE) model of the side glass combined with a generalized Statistical Energy Analysis (SEA) model of the interior cabin.

This paper makes a contribution toward a more efficient chassis durability process for the development of passenger cars, in which the simulation of relevant load data is a time-consuming part. This is especially due to the full vehicle model complexity which is usually determined by the demands of rough road simulations. However, for the load calculation on a racetrack, time saving model approaches that are more simplified might be sufficient. Our investigation comprises two levels of vehicle model complexity: one with all chassis parts modeled in a multibody system environment and one characteristic curve based model in an internal simulation environment. Both approaches consider an original chassis control system as a Software-in-the-Loop model. By the evaluation of real-world experiments the main influence factors in terms of durability are demonstrated. With the help of those highly sensitive durability criteria the measurement and simulation results are then compared.

The future emission regulation (BS V) in India is expected to create new challenges to meet the particulate matter (PM) limit for diesel cars. The upcoming emission norms will bring down the limit of PM by 80 % when compared to BS IV emission norms. The diesel particulate filter (DPF) is one of the promising technologies to achieve this emission target. The implementation of DPF system into Indian market poses challenges against fuel quality, driving cycles and warranty. Hence, it is necessary to do a detailed on-road evaluation of the DPF system with commercially available fuel under country specific drive cycles. Therefore, we conducted full vehicle durability testing with DPF system which is available in the European market to evaluate its robustness and reliability with BS III fuel (≤350ppm sulfur) & BS IV (≤50ppm sulfur) fuel under real Indian driving conditions.

Spark-ignition engine fuel standards have been put in place to ensure acceptable hot and cold weather driveability (HWD and CWD). Vehicle manufacturers and fuel suppliers have developed systems that meet our driveability requirements so effectively that drivers overwhelmingly find that their vehicles reliably start up and operate smoothly and consistently throughout the year. For HWD, fuels that are too volatile perform more poorly than those that are less volatile. Vapor lock is the apparent cause of poor HWD, but there is conflicting evidence in the literature as to where in the fuel system it occurs. Most studies have found a correlation between degraded driveability and higher dry vapor pressure equivalent or lower TV/L = 20, and less consistently with a minimum T50. For CWD, fuels with inadequate volatility can cause difficulty in starting and rough operation during engine warmup.

Highly automated driving (HAD) is under rapid development and will be available for customers within the next years. However the evidence that HAD is at least as safe as human driving has still not been produced. The challenge is to drive hundreds of millions of test kilometers without incidents to show that statistically HAD is significantly safer. One approach is to let a HAD function run in parallel with human drivers in customer cars to utilize a fraction of the billions of kilometers driven every year. To guarantee safety, the function under test (FUT) has access to sensors but its output is not executed, which results in an open loop problem. To overcome this shortcoming, the proposed method consists of four steps to close the loop for the FUT. First, sensor data from real driving scenarios is fused in a world model and enhanced by incorporating future time steps into original measurements.