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Finite element simulation (FE) makes it possible to analyze the structural dynamic behavior of vehicle seat structures in early design phases to meet Noise-Vibration-Harshness (NVH) requirements. For this purpose, linear simulations are usually used, which neglect many nonlinear mechanical properties of the real structure. These models are trimmed to fit global vibration behavior based on the complex description of contact or jointed definitions. Targeted design is therefore only possible to a limited extent. The aim of this work is to characterize the entire seat structure and its sub-components in order to identify the main contributors using experimental and simulative data. The Lagrange Multiplier Frequency Based Substructuring (LM-FBS) method is used for this purpose. Therefore, the individual subsystems of seat frame, seat backrest and headrest are characterized under different conditions.

Raising demands towards lightweight design paired with a loss of originally predominant engine noise pose significant challenges for NVH engineers in the automotive industry. From an aeroacoustic point of view, low frequency buffeting ranks among the most frequently encountered issues. The phenomenon typically arises due to structural transmission of aerodynamic wall pressure fluctuations and/or, as indicated in this work, through rear vent excitation. A possible workflow to simulate structure-excited buffeting contains a strongly coupled vibro-acoustic model for structure and interior cavity excited by a spatial pressure distribution obtained from a CFD simulation. In the case of rear vent buffeting no validated workflow has been published yet. While approaches have been made to simulate the problem for a real-car geometry such attempts suffer from tremendous computation costs, meshing effort and lack of flexibility.

The Noise Vibration and Harshness (NVH) characteristics and requirements of vehicles are changing as the automotive manufacturers turn their focus from developing and producing cars propelled by internal combustion engines (ICE) to electrified vehicles. This new strategic orientation enables them to offer products that are more efficient and environmentally friendly. Although electric powertrains have many advantages compared to their established predecessors they also bring new challenges that increase the difficulty of matching the high quality requirements of premium car producers especially regarding NVH. Electric motors are one of the most important sources of vibrations in electric vehicles.

Driving cycles are valuable tools for emissions calibration at engine and powertrain test beds. While generic velocity profiles were sufficient in the past, legislative changes and increasing complexity of powertrain and exhaust aftertreatment systems require a new approach: Realistically transient cycles - which include critical driving maneuvers and can be tailored to a specific powertrain configuration - are needed to optimize the emission behavior of the said powertrain. For the generation of realistic velocity profiles, the Markov chain approach has been widely used and described in literature. However, this approach, so far, has only been used to generate cycles that are statistically representative of a large database of real driving trips, which is typically not available during the early stages of development of a new powertrain.

Classical decentralized architectures based on large networks of microprocessor-based Electronic Control Units (ECU), namely those used in self-driving cars and other highly-automated applications used in the automotive industry, are becoming more and more complex. These new, high computational power demand applications are constrained by limits on energy consumption, weight, and size of the embedded components. The adoption of new embedded centralized electrical/electronic (E/E) architectures based on dynamically reconfigurable hardware represents a new possibility to tackle these challenges. However, they also raise concerns and questions about their safety. Hence, an appropriate evaluation must be performed to guarantee that safety requirements resulting from an Automotive Safety Integrity Level (ASIL) according to the standard ISO 26262 are met. In this paper, a methodology for the evaluation of dynamically reconfigurable systems based on centralized architectures is presented.

Model Order Reduction (MOR) methods such as Component Mode Synthesis (CMS) have been used in order to simulate large linear dynamic systems for many years and have reached a considerable level of saturation. These reduction methods have many advantages such as minimizing computational costs but also have restrictions. One of their disadvantages is that material damping characteristics can only be defined in form of Rayleigh damping. Another disadvantage is that the reduced order model can only represent one state of the structure determined in the generation process of the reduced matrices. In this paper we present a way to consider material damping in reduced matrices that contain one or more materials having different damping characteristics without the disadvantages of using Rayleigh damping.

The Deep Orange program immerses automotive engineering students into the world of an OEM as part of their 2-year graduate education. In support of developing the program’s seventh vehicle concept, the students studied the sponsoring brand essence, conducted market research, and made a heuristic assessment of competitor vehicles. The upfront research lead to the definition of target customers and setting vehicle level targets that were broken down into requirements to develop various vehicle sub-systems. The powertrain team was challenged to develop a scalable propulsion concept enabled by a common vehicle architecture that allowed future customers to select (at the point of purchase) among various levels of electrification best suiting their needs and personal desires. Four different configurations were identified and developed: all-electric, two plug-in hybrid electric configurations, and an internal combustion engine only.

Onboard diagnostic regulations require performance monitoring of diesel particulate filters used in vehicle aftertreatment systems. Delphi has developed a particulate matter (PM) sensor to perform this function. The objective of this sensor is to monitor the soot (PM) concentration in the exhaust downstream of the diesel particulate filter which provides a means to calculate filter efficiency. The particulate matter sensor monitors the deposition of soot on its internal sensing element by measuring the resistance of the deposit. Correlations are established between the soot resistance and soot mass deposited on the sensing element. Currently, the sensor provides the time interval between sensor regeneration cycles, which, with the knowledge of the exhaust gas flow parameters, is correlated to the average soot concentration.

The quiet nature of hybrid and electric vehicles has triggered developments in research, vehicle manufacturing and legal requirements. Currently, three countries require fitting an Approaching Vehicle Alerting System (AVAS) to every new car capable of driving without a combustion engine. Various other geographical areas and groups are in the process of specifying new legal requirements. In this paper, the design challenges in the on-going process of designing the sound for quiet cars are discussed. A proposal is issued on how to achieve the optimum combination of safety, environmental noise, subjective sound character and technical realisation in an iterative sound design process. The proposed sound consists of two layers: the first layer contains tonal components with their pitch rising along with vehicle speed in order to ensure recognisability and an indication of speed.

Delphi is developing a new combustion technology called Gasoline Direct-injection Compression Ignition (GDCI), which has shown promise for substantially improving fuel economy. This new technology is able to reuse some of the controls common to traditional spark ignition (SI) engines; however, it also requires several new sensors and actuators, some of which are not common to traditional SI engines. Since this is new technology development, the required hardware set has continued to evolve over the course of the project. In order to support this development work, a highly capable and flexible electronic control system is necessary. Integrating all of the necessary functions into a single controller, or two, would require significant up-front controller hardware development, and would limit the adaptability of the electronic controls to the evolving requirements for GDCI.

Bond wires are used in automotive electronic modules to carry current from external harness to components where flexibility under thermal cyclic loading is very essential between PCB (Printed Circuit Board) and connectors. They are very thin wires (few μm) made up of gold, aluminum or copper and have to undergo mechanical reliability to withstand extreme mechanical and thermal loads during different vehicle operation scenarios. Thermal reliability of bond wire is to make sure that it can withstand prescribed electric current under given boundary conditions without fusing thereby retaining electronic module's functionality. While carrying current, bond wire by virtue of its nature resists electric current flow and generates heat also called as joule heating. Joule heating is proportional to current flow and electrical resistance and if not handled properly can lead to thermal run away conditions.

The present paper reports on a study of the HVAC energy usage for an EREV (extended range electric vehicle) implementation of a localized cooling/heating system. Components in the localized system use thermoelectric (TE) devices to target the occupant's chest, face, lap and foot areas. A novel contact TE seat was integrated into the system. Human subject comfort rides and a thermal manikin in the tunnel were used to establish equivalent comfort for the baseline and localized system. The tunnel test results indicate that, with the localized system, HVAC energy savings of 37% are achieved for cooling conditions (ambient conditions greater than 10 °C) and 38% for heating conditions (ambient conditions less than 10 °C), respectively based on an annualized ambient and vehicle occupancy weighted method. The driving range extension for an electric vehicle was also estimated based on the HVAC energy saving.

The requirement of the start of the internal combustion engine (ICE) not only at vehicle standstill is new for full hybrid electric vehicles in comparison to conventional vehicles. However, the customer will not accept any deterioration with respect to dynamics and comfort. ICE-starting-systems and -strategies have to be designed to meet those demands. Within this research, a method was developed which allows a reproducible maneuver-based analysis of ICE-starts. In the first step, a maneuver catalogue including a customer-oriented maneuver program with appropriate analysis criteria was defined. Afterwards, the maneuvers were implemented and verified in a special test bench environment. Based on the method, two sample hybrid vehicles were benchmarked according to the maneuver catalogue. The benchmarking results demonstrate important dependencies between the criteria-based assessment of ICE-starts and the embedded ICE-starting-system and -strategy.

Modern exhaust systems contain not only a piping network to transport hot gas from the engine to the atmosphere, but also functional components such as the catalytic converter and turbocharger. The turbocharger is common place in the automotive industry due to their capability to increase the specific power output of reciprocating engines. As the exhaust system is a main heat source for the under body of the vehicle and the turbocharger is located within the engine bay, it is imperative that accurate surface temperatures are achieved. A study by K. Haehndel [1] implemented a 1D fluid stream as a replacement to solving 3D fluid dynamics of the internal exhaust flow. To incorporate the 3D effects of internal fluid flow, augmented Nusselt correlations were used to produce heat transfer coefficients. It was found that the developed correlations for the exhaust system did not adequately represent the heat transfer of the turbocharger.

Wind noise is a significant source of interior noise in automobiles at cruising conditions, potentially creating dissatisfaction with vehicle quality. While wind noise contributions at higher frequencies usually originate with transmission through greenhouse panels and sealing, the contribution coming from the underbody area often dominates the interior noise spectrum at lower frequencies. Continued pressure to reduce fuel consumption in new designs is causing more emphasis on aerodynamic performance, to reduce drag by careful management of underbody airflow at cruise. Simulation of this airflow by Computational Fluid Dynamics (CFD) tools allows early optimization of underbody shapes before expensive hardware prototypes are feasible. By combining unsteady CFD-predicted loads on the underbody panels with a structural acoustic model of the vehicle, underbody wind noise transmission could be considered in the early design phases.

The thermal prediction of a vehicle under-body environment is of high importance in the design, optimization and management of vehicle power systems. Within the pre-development phase of a vehicle's production process, it is important to understand and determine regions of high thermally induced stress within critical under-body components. Therefore allowing engineers to modify the design or alter component material characteristics before the manufacture of hardware. As the exhaust system is one of the primary heat sources in a vehicle's under-body environment, it is vital to predict the thermal fluctuation of surface temperatures along corresponding exhaust components in order to achieve the correct thermal representation of the overall under-body heat transfer. This paper explores a new method for achieving higher accuracy exhaust surface temperature predictions.

In vehicular mobility context, it is extremely important for the environmental sustainability that the available energy will be used as efficiently as possible, both in the use of internal combustion engines (ICE) as powertrain, as well in the application of Hybrid and Electric Vehicle Motors (HEV/EV). In this comparison, ICE has a lower efficiency when compared to electric motors, wasting much of the potential energy of the fuel in form of heat and noise. On the other hand, the electric vehicles face limitation in autonomy and recharge time, demanding for a more efficient use of energy stored in batteries. This study aims to present emerging technologies for reuse of energy within the automotive context, originally known as “Energy Harvesting” and “Renewable Energies”.

While the potential emissions and efficiency benefits of HCCI combustion are well known, realizing the potentials on a production intent engine presents numerous challenges. In this study we focus on identifying challenges and opportunities associated with a production intent cam-based variable valve actuation (VVA) system on a multi-cylinder engine in comparison to a fully flexible, naturally aspirated, hydraulic valve actuation (HVA) system on a single-cylinder engine, with both platforms sharing the same GDI fueling system and engine geometry. The multi-cylinder production intent VVA system uses a 2-step cam technology with wide authority cam phasing, allowing adjustments to be made to the negative valve overlap (NVO) duration but not the valve opening durations. On the single-cylinder HVA engine, the valve opening duration and lift are variable in addition to the NVO duration. The content of this paper is limited to the low-medium operating load region at 2000 rpm.

Spot, or distributed, cooling and heating is an energy efficient way of delivering comfort to an occupant in the car. This paper describes an approach to distributed cooling in the vehicle. A two passenger CFD model of an SUV cabin was developed to obtain the solar and convective thermal loads on the vehicle, characterize the interior thermal environment and accurately evaluate the fluid-thermal environment around the occupants. The present paper focuses on the design and CFD analysis of the energy efficient HVAC system with spot cooling. The CFD model was validated with wind tunnel data for its overall accuracy. A baseline system with conventional HVAC air was first analyzed at mid and high ambient conditions. The airflow and cooling delivered to the driver and the passenger was calculated. Subsequently, spot cooling was analyzed in conjunction with a much lower conventional HVAC airflow.

Aerodynamic performance assessment of automotive shapes is typically performed in wind tunnels. However, with the rapid progress in computer hardware technology and the maturity and accuracy of Computational Fluid Dynamics (CFD) software packages, evaluation of the production-level automotive shapes using a digital process has become a reality. As the time to market shrinks, automakers are adopting a digital design process for vehicle development. This has elevated the accuracy requirements on the flow simulation software, so that it can be used effectively in the production environment. Evaluation of aerodynamic performance covers prediction of the aerodynamic coefficients such as drag, lift, side force and also lift balance between the front and rear axle. Drag prediction accuracy is important for meeting fuel efficiency targets, prediction of front and rear lifts as well as side force and yawing moment are crucial for high speed handling.