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SAE paper 2013-01-0213 [1] described firefighting tests with Li-Ion traction batteries. However, additional knowledge and experience has been gained since then. In 2018 and 2019, DEKRA Accident Research and the Department of Anesthesiology of the University Medical Center Göttingen conducted crash tests far beyond standard with four battery electric vehicles. Three of the vehicles’ batteries were used to test a new method of firefighting. A specially designed lance was used to pierce the battery housing, which enabled water to be directly fed into the housings themselves. The method proved to be very effective, but the tests also showed some limitations. The information gleaned from this series of tests and experience gained from other tests was used as a basis for the formation of a multidisciplinary group of experts.

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.

In this paper a method for the identification of most significant vehicle parameters influencing the behavior of a lateral control system of autonomous car is presented. Requirements for the design stage of the controller need to consider many uncertainties in the plant. While most vehicle properties can be compensated by an appropriate tuning of the control parameters, other vehicle properties can change significantly during usage. The control system is evaluated based on performance measures. Analyzed parameters comprise functional tire characteristics, mass of the vehicle and position of its center of gravity. Since the parameters are correlated, but Sobol’ sensitivity analysis assumes decorrelated inputs, random variation yields no reasonable results. Furthermore, the variation of each parameter or set of parameters is not applicable since the numbers of required simulations is increased significantly according to input dimension.

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.

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.

An accurate model to predict the formation of fogging and defogging which occurs for low windshield temperatures is helpful for designing the air-conditioning system in a car. Using a multiphase flow approach and additional user-defined functions within the commercial CFD-software STAR-CCM+, a model which is able to calculate the amount of water droplets on the windshield from condensation and which causes the fogging is set up. Different parameters like relative humidity, air temperature, mass flow rate and droplet distributions are considered. Because of the condition of the windshield's surface, the condensation occurs as tiny droplets with different sizes. The distribution of these very small droplets must be obtained to estimate numerically the heat transfer coefficient during the condensation process to predict the defogging time.

Due to their high energy density, power density, and durability, lithium-ion (Li-ion) batteries are rapidly becoming the most popular energy storage method for electric vehicles. Difficulty arises in accurately estimating the amount of left capacity in the battery during operation time, commonly known as battery state of charge (SOC). This paper presents a comparative study between six different Equivalent Circuit Li-ion battery models and two different state of charge (SOC) estimation strategies. The Battery models cover the state-of-the-art of Equivalent Circuit models discussed in literature. The Li-ion battery SOC is estimated using non-linear estimation strategies i.e. Extended Kalman filter (EKF) and the Smooth Variable Structure Filter (SVSF). The models and the state of charge estimation strategies are compared against simulation data obtained from AVL CRUISE software.

The worldwide automotive industry is currently preparing for a market introduction of hydrogen-fueled powertrains. These powertrains in fuel cell electric vehicles (FCEVs) offer many advantages: high efficiency, zero tailpipe emissions, reduced greenhouse gas footprint, and use of domestic and renewable energy sources. To realize these benefits, hydrogen vehicles must be competitive with conventional vehicles with regards to fueling time and vehicle range. A key to maximizing the vehicle's driving range is to ensure that the fueling process achieves a complete fill to the rated Compressed Hydrogen Storage System (CHSS) capacity. An optimal process will safely transfer the maximum amount of hydrogen to the vehicle in the shortest amount of time, while staying within the prescribed pressure, temperature, and density limits. The SAE J2601 light duty vehicle fueling standard has been developed to meet these performance objectives under all practical conditions.

The number of full electric and hybrid electric vehicles is rapidly growing [1][2][3]. The new technologies accompanying this trend are increasingly becoming a focal point of interest for rescue services. There is much uncertainty about the right techniques to free trapped occupants after an accident. The same applies to vehicle fires. Can car fires involving vehicles with a lithium ion traction battery be handled in the same way as conventional vehicle fires? Is water the right extinguishing agent? Is there a risk of explosion? There are many unanswered questions surrounding the topic of electric vehicle safety. The lack of information is a breeding ground for rumours, misinformation and superficial knowledge. Discussions on various internet platforms further this trend. Tests were conducted on three lithium ion traction batteries, which were fuel-fired until burning on their own. The batteries were then extinguished with water, a surfactant and a gelling agent.

Since the last decade, alternative powertrains are playing an important role in the strategy of car manufacturers. One important goal is the introduction of zero emission powertrains. These powertrain systems raise increasing political and public interest with the hydrogen fuel cell engine being the most competitive powertrain technology. During the development of this new technology, all the functional aspects including the automotive vehicle safety need to be considered. Hydrogen sensors are installed in the system to optimize the performance of a hydrogen fuel cell system and to enhance the safety concept. New results of sensor optimization and innovative test and development methods based on real vehicle data are described in this paper.

NH₃/urea SCR is a very effective and widely used technology for the abatement of NOx from diesel exhaust. The SCR mechanism is well understood and the catalyst behavior can be predicted by mathematical models - as long as operation above the temperature limit for AdBlue® injection is considered. The behavior below this level is less understood. During the first seconds up to minutes after cold start, complete NOx abatement can be observed over an SCR catalyst in test bench experiments, together with a significant increase in temperature after the converter (ca. 100 K). In this work these effects have been investigated over a monolith Cu-zeolite SCR catalyst. Concentration step experiments varying NO, NO₂ and H₂O have been carried out in lab scale, starting from room temperature. Further, the interaction of C₃H₆ and CO with NOx over the SCR has been investigated.

In order to reduce fuel consumption in Fuel Cell Electric Vehicles, effective distribution of power demand between Fuel Cell and Battery is required. Energy management strategies can improve fuel economy by meeting power demand efficiently. This paper explains development of various energy management strategies for Fuel Cell Electric Vehicle with Lithium Ion Battery. Drive cycles used for optimization and analysis of the strategies are New European Drive cycles (NEDC), Japanese Drive cycles (JAP1015), City Drive cycles, Highway Drive cycles (FHDS) and Federal Urban Drive cycles (FUDS). All Fuel consumption and ageing calculations are done using backward model implemented in MATLAB/SIMULINK.

A fuel cell system consists of a stack, a hydrogen fuel supply and an air supply system. This provides the required air flow and pressure which allows the stack to properly react on the cathode side to recombine Oxygen with the Hydrogen's protons and electrons resulting in water and heat. In addition the air flow and pressure are supporting directly or indirectly the water management. In this paper different air supply systems for automotive application developed by NuCellSys are compared: screw compressor and electrical turbo charger. Different technologies and control strategies allow the fuel cell system integrator to find the optimum between performances, weight, volume and cost. The authors describe the challenges and the new frontier of air supply systems for automotive fuel cell system application.

Digital or virtual prototyping by means of a multibody simulation model (MBS) is a standard part of the automotive design process. A high-fidelity model is built and often correlated against test data to increase its accuracy. Once built the MBS model can then be used for high fidelity analysis in ride comfort, handling as well as durability. Next to the MBS model, current industry practice is to develop a reduced degree of freedom model for the design and validation of control or intelligent systems. The models used in the control system design are required to execute in hardware-in-the-loop (HIL) simulations where it is necessary to run real-time. The reason for the creation of the reduced degree of freedom models so far has been that the high-fidelity or off-line model does not execute fast enough to be used in an HIL simulation.

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

The continuously integration of electrics and electronics (EE) in the last decades is one of the main key drivers for innovation and business success of the Automotive OEMs. This is also applicable for truck manufacturers. On the other side factors like the rising vehicle complexity, number of variants and the warranty costs for EE issues are increasing the pressure on the engineering teams responsible for the mechatronic systems. To address these issues one of the key activities in the European market (focus on Germany) during the last decade was to introduce industry-wide standards for the data transfer of wiring harness data between OEM and harness supplier. In this paper the benefits and technical background of using the standards KBL and KOMP formats within the MB-Trucks brand will be presented. Moreover the role of the Information Technology (IT) will be explained in detail.

The economic challenges and environmental imperatives facing the trucking and automobile industries today all point to a pressing need to improve fuel efficiency. Due to increasing volatility of fuel supplies, prices and a growing interest in reducing greenhouse gas emissions, fuel efficiency has taken on new urgency. In the long-haul trucking industry this is especially important given the fact that fuel accounts for a significant share of fleet operating costs. To this end Daimler and NAVTEQ have developed a system to improve fuel economy and reduce CO₂ emissions through the integration of digital map data into Advanced Driver Assistance Systems or ADAS. Digital road map attributes, especially road slope have been demonstrated to enable powertrain controls to anticipate road inclination changes and use this information to predictively enhance load management optimization versus the reactive approach afforded by current technology.

In this study the numerical simulation of the flow through an alternator inside an engine compartment of a passenger car is investigated. Specifically the interaction of the flow through the alternator with the flow through the engine compartment is explored in detail. The results are compared with a corresponding numerical simulation of an alternator in a surrounding of a test facility and with a numerical simulation of the flow through an engine compartment without taking into account the internal flow through the alternator. Finally the air temperature near the alternator and also the temperature of some components inside the alternator are compared with experimental values measured during a typical load case used for the thermal protection of the passenger car.

Tire mark analysis is an important factor in accident reconstruction. A precise determination of pre- and postcrash speeds as well as longitudinal and lateral accelerations from tire marks contributes significantly to a reliable accident reconstruction. Continuous advancements in tire and vehicle technology – in particular with respect to modern control systems such as anti-lock braking systems (ABS) – raises the question what role tire marks play in accident reconstruction today. Moreover, this accompanies the question to what extent potential interventions by vehicle control systems such as the electronic stability program (ESP®) resp. the electronic stability control (ESC) can be identified in a tire mark. The widespread use of these systems today makes them increasingly important in accident reconstruction.

A numerical model for a diesel oxidation catalyst (DOC) is presented. It is based on a spatially 1D, physical and chemically based modeling of the relevant processes within the catalytic monolith. A global reaction kinetic approach has been chosen to describe the chemical reactions. Water condensation and evaporation was also considered, in order to predict the cold start behavior. Reaction kinetic parameters have been evaluated from a series of laboratory experiments. A correlation between the kinetic parameters and the noble metal loading was developed. The model was used in combination with a SCR-Model to study the influence of changes of noble metal loading and DOC volume on the overall transient NOx performance of a DOC+DPF+SCR system.