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Self-learning energy management is a promising concept, which optimizes real-world system performance by automated, on-line adaptation of control settings. In this work, the potential of self-learning capabilities related to optimization is studied for energy management in Plug-in Hybrid Electric Vehicles (PHEV). These vehicles are of great interest for the transport sector, since they combine high fuel efficiency with last mile full-electric driving. We focus on a specific use case: PHEV operation through future Zero Emission (ZE) zones of cities. As a first step towards self-learning control, we introduce a novel, adaptive supervisory controller that combines modular energy and emission management (MEEM) and deals with varying constraints and system uncertainty. This optimal control strategy is based on Pontryagin’s Minimum Principle and maximizes overall energy efficiency.

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.

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.

The Deep Orange program is a concept vehicle development program focused on providing hands-on experience in design, engineering, prototyping and production planning as part of students’ two-year MS graduate education. Throughout this project, the team was challenged to create innovative concepts during the ideation phase as part of building the running vehicle. This paper describes the usability studies performed on two of the vehicle concepts that require driver interaction. One concept is a human machine interface (HMI) that uses a holographic companion that can act as a concierge for all functions of the vehicle. After creating a prototype using existing technologies and developing a user interface controlled by hand gestures, a usability study was completed with older adults. The results suggest the input method was not intuitive. Participants demonstrated better performance with tasks using discrete hand motions in comparison to those that required continuous motions.

With the adoption of the Worldwide harmonized Light Vehicles Test Procedure (WLTP) and the Real Driving Emissions (RDE) regulations for testing and monitoring the vehicle pollutant emissions, as well as CO2 and fuel consumption, the gap between real world and type approval performances is expected to decrease to a large extent. With respect to CO2, however, WLTP is not expected to fully eliminate the reported 40% discrepancy between real world and type approval values. This is mainly attributed to the fact that laboratory tests take place under average controlled conditions that do not fully replicate the environmental and traffic conditions experienced over daily driving across Europe. In addition, any uncertainties of a pre-defined test protocol and the vehicle operation can be optimized to lower the CO2 emissions of the type approval test. Such issues can be minimized in principle with the adoption of a real-world test for fuel consumption.

This paper presents a methodology and tool that stochastically generates drive cycles based on measured data, with the purpose of testing and benchmarking light duty vehicles in a simulation environment or on a test-bench. The WLTP database, containing real world driving measurements, was used as input data. Consequently cycles that contain typical accelerations per velocity and road types are generated, such that these cycles are representative to real driving behavior. The stochastic drive cycle generator is developed in Matlab and is based on Markov processes. Two separate stochastic generators are used: one for generating the road type and one for generating the vehicle acceleration. First, a random road type profile is generated from the four different road types that are considered in the WLTP database: urban, rural, motorway and high-motorway, each of them with sub-road types based on different velocity bins.

Heavy-duty diesel engines are used in different application areas, like long-haul, city distribution, dump truck and building and construction industry. For these wide variety of areas, the engine performance needs to comply with the real-world legislation limits and should simultaneously have a low fuel consumption and good drivability. Meeting these requirements takes substantial development and calibration effort, where an optimal fuel consumption for each application is not always met in practice. TNO's Integrated Emission Management (IEM) strategy, is able to deal with these variations in operating conditions, while meeting legislation limits and obtaining on-line cost optimization. Based on the actual state of the engine and aftertreatment, optimal air-path setpoints are computed, which balances EGR and SCR usage.

Efforts in aerodynamic optimization of road vehicles have been steadily increasing in recent years, mainly focusing on the reduction of aerodynamic drag. Of a car's total drag, wheels and wheel houses account for approx. 25 percent. Consequently, the flow around automotive wheels has lately been investigated intensively. Previously, the authors studied a treaded, deformable, isolated full-scale tire rotating in contact with the ground in the wind tunnel and using the Lattice-Boltzmann solver Exa PowerFLOW. It was shown that applying a common numerical setup, with velocity boundary condition prescribed on the tread, significant errors were introduced in the simulation. The contact patch separation was exaggerated and the flow field from wind tunnel measurements could not be reproduced. This investigation carries on the work by examining sensitivities and new approaches in the setup.

Pedestrians and cyclists are the most unprotected road users and their injury risk in case of accidents is significantly higher than for other road users. The understanding of the influence and sensitivity between important variables describing a pedestrian crash is key for the development of more efficient and reliable safety systems. This paper reflects the related work carried out within the AsPeCSS project. The results summarized out of virtual and physical tests provide valuable information for further development. 1168 virtual and 120 physical tests were carried out with adult and child pedestrian headform as well as upper and lower legform impactors representatives of 4 different vehicle front geometries in a wide range of impact speeds, angles and locations. This test matrix was based on previous work carried out within the AsPeCSS project.

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.

Over the past 30 years, the computer-aided engineering (CAE) tools have been applied extensively in the automotive industry. In order to accelerate time-to-market while coping with legal limits that have become increasingly restrictive over the last decades, CAE has become an indispensable tool covering all major fields in a modern automotive product design process. However, when tackling complex real-life engineering problems, the computational models might become rather involved and thus less efficient. Therefore, the overall trend in the automotive industry is currently heading towards combined approaches, which allow the best of the both worlds, namely the experimental measurement and numerical simulation, to be merged into one integrated scheme. In this paper, the so-called patch transfer function (PTF) approach is adopted to solve coupled vibro-acoustic problems. In the PTF scheme, the interfaces between fluid and structure are discretised in terms of patches.

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.

Plug-In Hybrid Electric Vehicles (PHEV) are becoming increasingly important as an intermediate step on the roadmap to Battery Electric Vehicles (BEV). Li-Ion is the most important battery technology for future hybrid and electrical vehicles. Cycle life of batteries for automotive applications is a major concern of design and development on vehicles with electrified powertrain. Cell manufacturers present various cell chemistries based on Li-Ion technology. For choosing cells with the best cycle life performance appropriate test methods and criteria must be obtained. Cells must be stressed with accelerated aging methods, which correlate with real life conditions. There is always a conflict between high accelerating factors for fast results on the one hand and best accordance with reality on the other hand. Investigations are done on three different Li-Ion cell types which are applicable in the use of PHEVs.

What are the requirements of customers in an urban environment? What will sustainable mobility look like in the future? This presentation gives an overview of the integrated approach used by BMW to develop the BMW i3 - a purpose-built battery electric vehicle. Very low driving resistances for such a vehicle concept enable the delivery of both impressive range and driving excitement. A small optional auxiliary power unit offers range security for unexpected situations and opens up BEVs to customers who are willing to buy a BEV but are still hesitant due to range anxiety. Additional electric vehicles sold to the formerly range anxious will create additional electric miles. Presenter Franz Storkenmaier, BMW Group

Unsteady aerodynamic flow phenomena are investigated in the wind tunnel by oscillating a realistic 50% scale model around its vertical axis. Thus the model is exposed to time-dependent flow conditions at realistic Reynolds and Strouhal numbers. Using this setup unsteady aerodynamic loads are observed to differ significantly from quasi-steady loads. In particular, the unsteady yaw moment exceeds the quasi-steady approximation by 80%. On the other hand, side force and roll moment are over predicted by quasi-steady approximation but exhibit a significant time delay. Using hotwire anemometry, a delayed reaction of the wake flow of Δt/T = 0.15 is observed, which is thought to be the principal cause for the differences between unsteady and quasi-steady aerodynamic loads. A schematic mechanism explaining these differences due to the delayed reaction of the wake flow is proposed.

Unsteady aerodynamic flow phenomena are investigated in a wind tunnel by oscillating a realistic 50% scale model around the vertical axis. Thus the model is exposed to time-dependent flow conditions at realistic Reynolds and Strouhal numbers. Using this setup unsteady aerodynamic loads are observed to differ significantly from quasi steady loads. In particular, the unsteady yaw moment exceeds the quasi steady approximation significantly. On the other hand, side force and roll moment are over predicted by quasi steady approximation but exhibit a significant time delay. Part 2 of this study proves that a delayed and enhanced response of the surface pressures at the rear side of the vehicle is responsible for the differences between unsteady and quasi steady loads. The pressure changes at the vehicle front, however, are shown to have similar amplitudes and almost no phase shift compared to quasi steady flow conditions.

Evaluation of safety benefits is an essential task during design and development of pedestrian protection systems. Comparative evaluation of different safety concepts is facilitated by a common metric taking into account the expected human benefits. Translation of physical characteristics of a collision, such as impact speed, into human benefits requires reliable and preferably evidence-based injury models. To this end, the dependence of injury severity of body regions on explanatory factors is quantified here using the US Pedestrian Crash Data Study (PCDS) for pedestrians in frontal vehicle collisions. The explanatory and causal factors include vehicle component characteristics, physiological and biomechanical variables, and crash parameters. Severe to serious injuries most often involve the head, thorax and lower extremities.

This paper presents a new approach to analyzing and developing low-drag cooling systems. A relation is derived which describes cooling drag by a number of contributions. Interference drag clearly can be identified as one of them. Cooling system parameters can be assigned to different terms of the relation, so that differences due to parameter variations of the individual drag contributions can be estimated. In order to predict the interference-drag dependency on the outlet location and the local outlet mass flow, an extensive study on a standard BMW sedan has been carried out, both experimentally and by CFD. The results show the importance of providing consistent outflow conditions which take into account the outlet location and flow direction, in order to minimize cooling drag.

Two major trends can be identified for powertrain control in the next decade. The legislation will more and more focus on in-use emissions. Together with the global trend to reduce the CO₂ emissions, this will lead to an integral drive train approach. To develop and validate this integral drive train approach, the need for a new chapter in powertrain testing arises. The climatic-altitude chamber, suited for heavy vehicles, serves a wide variety of testing needs. Ambient temperature can be controlled between -45°C and +55°C and ambient pressure can be reduced up to a level found at an altitude to 4000 meters. The chamber's dynamometers enable transient testing of heavy-duty engines and vehicles and the chamber is equipped with a comprehensive array of emission measurement capabilities, working under extreme conditions.

Injury assessment reference values (IARV) predicting neck injuries are currently not available for side facing seated aircraft passengers in crash conditions. The aircraft impact scenario results in inertial loading of the head and neck, a condition known to be inherently different from common automotive side impact conditions as crash pulse and seating configurations are different. The objective of this study is to develop these IARV for the European Side Impact Dummy-2 (ES-2) previously selected by the US-FAA as the most suitable ATD for evaluating side facing aircraft seats. The development of the IARV is an extended analysis of previously published PMHS neck loads by identifying the most likely injury scenarios, comparing head-neck kinematics and neck loads of the ES2 versus PMHS, and development of injury risk curves for the ES2. The ES2 showed a similar kinematic response as the PMHS, particularly during the loading phase.