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Bicycle-drawn cargo trailers with an electric drive to enable the transportation of high cargo loads are used as part of the last-mile logistics. Depending on the load, the total mass of a trailer can vary between approx. 50 and 250 kg, potentially more than the mass of the towing bicycle. This can result in major changes in acceleration and braking behavior of the overall system. While existing systems are designed primarily to provide sufficient power, improvements are needed in the powertrain control system in terms of driver safety and comfort. Hence, we propose a novel prototype that allows measurement of the tensile force in the drawbar which can subsequently be used to design a superior control system. In this context, a sinusoidal force input from the cyclist to the trailer according to the cadence of the cyclist is observed. The novelty of this research is to analyze whether torque impulses of the cyclist can be reduced with the help of Model Predictive Control (MPC).

Deep neural network models have been widely used for environment perception of intelligent vehicles. However, due to models’ innate probabilistic property, the lack of transparency, and sensitivity to data, perception results have inevitable uncertainties. To compensate for the weakness of probabilistic models, many pieces of research have been proposed to analyze and quantify such uncertainties. For safety-critical intelligent vehicles, the uncertainty analysis of data and models for environment perception is especially important. Uncertainty estimation can be a way to quantify the risk of environment perception. In this regard, it is essential to deliver a comprehensive survey. This work presents a comprehensive overview of uncertainty estimation in deep neural networks for environment perception of intelligent vehicles.

In order to predict reality as accurately as possible leads to the fact that numerical models in automotive vibroacoustic problems become increasingly high dimensional. This makes applications with a large number of model evaluations, e.g. optimization tasks or uncertainty quantification hard to solve, as they become computationally very expensive. Engineers are thus faced with the challenge of making decisions based on a limited number of model evaluations, which increases the need for data-efficient methods and reduced order models. In this contribution, variational autoencoders (VAEs) are used to reduce the dimensionality of the vibroacoustic model of a vehicle body and to find a low-dimensional latent representation of the system.

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 recent growth of available computational resources has enabled the automotive industry to utilize unsteady Computational Fluid Dynamics (CFD) for their product development on a regular basis. Over the past years, it has been confirmed that unsteady CFD can accurately simulate the transient flow field around complex geometries. Concerning the aerodynamic properties of road vehicles, the detailed analysis of the transient flow field can help to improve the driving stability. Until now, however, there haven’t been many investigations that successfully identified a specific transient phenomenon from a simulated flow field corresponding to driving stability. This is because the unsteady flow field around a vehicle consists of various time and length scales and is therefore too complex to be analyzed with the same strategies as for steady state results.

The thermal and emission efficiency of diesel engines depends to a large extent on the quality of fuel injection. However, over engine lifetime, injection rate and quality will change due to adverse nozzle aging effects, such as coking or cavitation. In this study, we discuss the influences of these effects on injection and heat release rate. The injection rates of previously unused nozzles and a nozzle that had been operated in a vehicle engine were compared in order to clarify the impact of aging effects. The key to the detection of alterations of injection nozzles is the identification of strongly correlating parameters. As a first step, an instrumented injector was set up to measure fuel pressure inside the feed line of the injector and the lift of the control piston. Different nozzles showed a distinguishable control piston motion depending on their different geometric specifications, which also affect the injection rates.

Over the past years, the question as to what may be the powertrain of the future has become ever more apparent. Aiming to improve upon a given technology, the internal combustion engine still offers a number of development paths in order to maintain its position in public and private mobility. In this study, an innovative combustion process is investigated with the goal to further approximate the ideal Otto cycle. Thus far, similar approaches such as Homogeneous Charge Compression Ignition (HCCI) shared the same objective yet were unable to be operated under high load conditions. Highly increased control efforts and excessive mechanical stress on the components are but a few examples of the drawbacks associated with HCCI. The approach employed in this work is the so-called Spark Assisted Compression Ignition (SACI) in combination with a pre-chamber spark plug, enabling short combustion durations even at high dilution levels.

The effectiveness of ADAS addressing property damage has an increasing impact on car manufacturers, insurers and customers, as accident avoidance or mitigation can lead to loss reduction. In order to obtain benefits, it is essential that ADAS primarily address monetarily relevant accident scenarios. Furthermore, sensor technologies and algorithms have to be configured in a way that relevant accident situations can be sufficiently avoided at reasonable system costs. A new methodology is developed to identify and configure monetarily effective parameters for ADAS during parking and maneuvering. ADAS parameters e.g. relevant accident scenarios, required crash avoidance speeds and different sensor layouts are analyzed and evaluated using a real-world in-depth accident database of insurance claims provided by Allianz Center for Technology and Allianz Automotive Innovation Center. For this purpose, a sensitivity analysis is conducted to identify most monetarily effective accident scenarios.

In times when automated driving is becoming increasingly relevant, dynamic simulators present an appropriate simulation environment to faithfully reproduce driving scenarios. A realistic replication of driving dynamics is an important criterion to immerse persons in the virtual environments provided by the simulator. Motion Cueing Algorithms (MCAs) compute the simulator’s control input, based on the motions of the simulated vehicle. The technical restrictions of the simulator’s actuators form the main limitation in the execution of these input commands. Typical dynamic simulators consist of a hexapod with six degrees of freedom (DoF) to reproduce the vehicle motion in all dimensions. Since its workspace dimensions are limited, significant improvements in motion capabilities can be achieved by expanding the simulator with redundant DoF by means of additional actuators.

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.

Aging effects such as coking or erosive damage that occur in fuel injection nozzles are known to deteriorate the engine performance. This article proposes an optimization method to compensate for injector aging and to control the combustion behavior over engine lifetime by adapting the injection strategy. First, a control-oriented combustion model is presented, which takes the condition of the injection nozzle into account. In combination with a simulation model of the entire fuel injection system from a previous study, the model is capable of predicting the heat release rate (HRR) at different working conditions. Measurements with a single-cylinder diesel engine were performed, using injectors with modified and aged nozzles, to validate the proposed combustion model and particularly to analyze the influence of injector aging. Using the simulation model, optimal injection strategies were obtained by applying a line search optimization scheme to recover a reference HRR trajectory.

In order to fulfill future exhaust emission regulations, the variety of subsystems of internal combustion engines is progressively investigated and optimized in detail. The present article mainly focuses on studies of the flow field and the resulting discharge coefficients of the intake and exhaust valves and ports. In particular, the valves and ports influence the required work for the gas exchange process, as well as the cylinder charge and consequently highly impact the engine’s performance. For the evaluation of discharge coefficients of a modern combustion engine, a stationary flow test bench has been set up at the Chair of Internal Combustion Engines (LVK) of the Technical University of Munich (TUM). The setup is connected to the test bench’s charge air system, allowing the adjustment and control of the system pressure, as well as the pressure difference across the particular gas exchange valve.

Improving fuel efficiency while meeting relevant emission limits set by emissions legislation is among the main objectives of engine development. Simultaneously the development costs and development time have to be steadily reduced. For these reasons, the high demands in terms of quality and validity of measurements at the engine test bench are continuously rising. This paper will present a new methodology for efficient testing of an industrial combustion engine in order to improve the process of decision making for combustion-relevant component setups. The methodology includes various modules for increasing measurement quality and validity. Modules like stationary point detection to determine steady state engine behavior, signal quality checks to monitor the signal quality of chosen measurement signals and plausibility checks to evaluate physical relations between several measurement signals ensure a high measurement quality over all measurements.

This study discusses model-based injection rate estimation in common rail diesel injectors exhibiting aging phenomena. Since they result in unexpected injection behavior, aging effects like coking or cavitation may impair combustion performance, which justifies the need for new modeling and estimation approaches. To predict injection characteristics, a simulation model for the bottom section of the injector is introduced, with a main focus on modeling the hydraulic components. Using rail pressure and control piston lift as inputs, a reduced model is then derived in state-space representation, which may be used for the application of an observer in hardware-in-the-loop (HIL) environments. Both models are compared and validated with experimental data, with which they show good agreement. Aging effects and nozzle wear, which result in model uncertainties, are considered using a fault model in combination with an extended Kalman filter (EKF) observer scheme.

This paper presents results on how the Equivalent Consumption Minimization Strategy (ECMS) penalty factor effects Lithium ion battery aging. The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’. Vehicle simulation using multiple combinations of highway and city drive cycles. For each combination of drive cycles, six ECMS penalty factor values are used. Battery aging is evaluated using a semi-empirical model combined with accumulated Ah-throughput method which uses, as an input, the battery state of charge trajectory from the vehicle simulations. The tradeoff between fuel cost and battery aging cost is explicitly displayed. In addition, the results provide insight into how driving behavior affects battery aging. The paper concludes with a discussion of the optimal balance between fuel cost and battery aging.

The increasing complexity of automotive functions which are necessary for improved driving assistance systems and automated driving require a change of common vehicle architectures. This includes new concepts for E/E architectures such as a domain-oriented vehicle network based on powerful Domain Control Units (DCUs). These highly integrated controllers consolidate several applications on different safety levels on the same ECU. Hence, the functions depend on a strictly separated and isolated implementation to guarantee a correct behavior. This requires middleware layers which guarantee task isolation and Quality of Service (QoS) communication have to provide several new features, depending on the domain the corresponding control unit is used for. In a first step we identify requirements for a middleware in automotive DCUs. Our goal is to reuse legacy AUTOSAR based code in a multicore domain controller.

This paper presents a phenomenological and semi-empirical simulation model to predict the injection rate of a diesel solenoid valve injector based on a few injection quantity measurements and indications (EMI). The approximate injection rate will be used as the input data for a subsequent model, which simulates the rate of heat release (ROHR). The injection rate model encompasses algebraic relations and differential equations deviating from the equations of motion and conservation, which describes the characteristic processes in the injector by using modular submodules. The process and its assumptions are explained step by step for each submodule. In addition, the injection rate predictions are presented and compared with experimental results arising from the selected reference solenoid valve injector.

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.

Aging effects such as coking or cavitation in the nozzle of common rail (CR) diesel injectors deteriorate combustion performance. This is of particular relevance when it comes to complying with emission legislation and demonstrates the need for detecting and compensating aging effects during operation. The first objective of this paper is to analyze the influence of worn nozzles on the injection rate. Therefore, measurements of commercial solenoid common rail diesel injectors with different nozzles are carried out using an injection rate analyzer of the Bosch type. Furthermore, a fault model for typical aging effects in the nozzle of the injector is presented together with two methods to detect and identify these effects. Both methods are based on a multi-domain simulation model of the injector. The needle lift, the control piston lift and the pressure in the lower feed line are used for the fault diagnosis.

Among the issues affecting the design process of a vehicle, there is the lack of multidisciplinary knowledge among the different teams involved. This often leads to the risk of loosing important key points from the initial concept idea of designers to the final vehicle package definition made by engineers. Therefore, this study builds up a method based on parameters defining exterior aesthetic priorities according to car segment to support engineers involved in the automotive design process. In particular, during the early design-engineering phase, this method should help them to understand better vehicle proportions defined by designers. This work is currently used in the course of design and simulation of road vehicles (Chair of Automotive Technology, TUM) to explain fundamentals of automotive design.