Automotive and Engine Technology最新文献

A new tire measurement procedure needs to be developed due to the optimization of the predictable recommendation of tire validity with regard to high-speed sensitivity (HSS). The high-speed sensitivity of tires describes the robustness, stability and controllability of a vehicle against disturbances at high speeds up to 200 kph. The high-speed sensitivity can be roughly estimated using the tire cornering stiffness. The definition of a new tire test procedure for cornering stiffness measurements at 200 kph aims to map a realistic driver profile [driver profile: average driving behavior of car drivers (no trained drivers).] and driving behavior as well as handling characteristics including a real test track without violating the tire validity limits (temperature, friction, etc.). Attention has to be paid to the short duration of the test procedure. A new tire test procedure is introduced which was developed for cornering stiffness measurements at high speeds up to 200 kph to better predict the high-speed behavior of tires on the test bench (here: external drum test bench).

The new concept of the self-propelled driving simulator comprises a hexapod, a yaw joint and a wheel-based motion platform with four individually steerable wheels. This concept provides a theoretically unlimited motion range, which especially enables highly dynamic drive maneuvers. To ensure an omnidirectional motion, the motion platform has to accelerate instantly in any direction. This requirement leads to the main challenges in the control system of the simulator: taking into account the nonlinear and transient tire characteristics and generating the target accelerations as expected by the driver. According to these requirements, the Motion Control is only for controlling the horizontal dynamics of the motion platform. The Motion Control presented in this paper includes various model definitions, especially regarding the essential tire characteristics considered within an extended HSRI (Highway Safety Research Institute) tire model. The Motion Control as Two-Degrees-of-Freedom control contains a Feedforward for generating target body forces, a Control Allocation for an optimal force distribution to the wheels, a Single Wheel Control as a specific control of the tire forces, and a Compensation Control on acceleration level. Investigation of this control by simulation, using a simplified reference model, already revealed a high controller performance regarding accuracy and quality. The optimal force distribution leads to an equal adhesion utilization and the Compensation Control compensates the remaining Single Wheel Control deviations. Difficulties only occur for the steering angle in the case of low velocity up to a standstill. Due to the exact input–output linearization, the Single Wheel Control leads to a singularity and instability. Therefore, the steering angle requires exceptional control in this case.

In this work, the experimental results that appeared in the recent published article “Current experimental developments in 48 V-based CI-driven SUVs in response to expected future EU7 legislation” are used to create a proper system simulation model with the simulation platform AVL CRUISE(^text {TM}) M. This simulation model is then used to perform a system validation in order to evaluate the configuration with a straight-four compression ignition (CI) engine and the selected exhaust aftertreatment system (EAS). The mild hybrid electric vehicle (MHEV) has an 48 V P2 architecture and an 8-gear dual-clutch transmission (DCT) as a powertrain configuration. In addition to evaluating the 48 V potential, the simulation is performed with a conventional 12 V configuration, but also including an electrically heated catalyst (EHC). As boundary conditions for the simulation, we use the different engine operating mode (EOM) calibrations from the test bed to trigger the dedicated operation modes of the internal combustion engine (ICE). For the exhaust aftertreatment system (EAS), an optimization loop is performed to obtain a layout which will be near a serial production. This includes optimizing the heat losses and reducing the thermal mass of the canning. Beside the plant models, a hybrid control unit (HCU) is used, which includes an exhaust aftertreatment system coordinator (EASC). With these functionalities, the EOMs, electrically heated catalyst (EHC), electric machine (EM) and dosing control unit (DCU) are optimized to obtain the lowest possible nitrogen oxides (NO_x) with an carbon dioxide (CO(_{2})) reduction potential. The targets for the emission limits are defined on the basis of the available information from the Consortium for ultra-Low Vehicle Emissions (CLOVE) and International Council on Clean Transportation (ICCT) proposals.

In the strive for the climate-neutral and ultra-low emission vehicle powertrains of the future, synthetic fuels produced from renewable sources will play a major role. Polyoxymethylene dimethyl ethers (POMDME or “OME”) produced from renewable hydrogen are a very promising candidate for zero-impact emissions in future CI engines. To optimize the utilisation of these fuels in terms of efficiency, performance and emissions, it is not only necessary to adapt the combustion parameters, but especially to optimize the injection and mixture formation process. In the present work, the spray break-up behavior and mixture formation of OME fuel is investigated numerically in 3D CFD and validated against experimental data from optical measurements in a high pressure/high temperature chamber using Schlieren and Mie scattering. For comparison, the same operating points using conventional diesel fuel were measured in the optical chamber, and the CFD modeling was optimized based on these data. To model the spray-breakup phenomena reliably, the primary break-up model according to Fischer is used, taking into account the nozzle internal flow in a detailed calculation of the disperse droplet phase. As OME has not yet been investigated very intensively with respect to its chemico-physical properties, chemical analyses of the substance properties were carried out to capture the most important parameters correctly in the simulation. With this approach, the results of the optical spray measurement could be reproduced well by the numerical model for the cases studied here, laying the basis for further numerical studies of OME sprays, including real engine operation.

This work presents a new approach to design and validate an economical lightweight multi-material roof-integrated vehicle door concept made of long-fiber thermoplastics (LFT) and metals with the consideration of package constrain, critical static and crash loading cases. A novel “two-ring” door structure is introduced, which consists of a major load-bearing region and a minor load-bearing but highly function-integrated region. This concept design concentrates on using cost-efficient lightweight materials, such as aluminum, LFTs and uni-directional tapes (UD-Tapes), as well as corresponding mass-production methods. Using the topology and parameter optimization along with the load anisotropy analysis, the rib structure on the door concept is optimized and the effective usage of UD-Tapes is guaranteed. In comparison to the steel reference, the final LFT-metal multi-material door concept achieves 20% weight reduction with a comparable or improved mechanical performance.

Since the potential for reducing CO₂ emissions from fossil fuels is limited, suitable CO₂-neutral fuels are required for applications which cannot reasonably be electrified, and therefore still rely on internal combustion engines in the future. Potential fuel candidates for CI engines are either paraffinic diesel fuels or new fuels like POMDME (polyoxymethylene dimethyl ether, short “OME”). Besides, also blends of these two types of fuels might be of interest. While many studies have been conducted on OME blends with fossil diesel fuel, the research on HVO–OME blends has been less extensive to date.

In the current work, pure OME and HVO–OME blends are investigated in a single-cylinder research engine. The test results of the various fuel blend formulations are compared and evaluated, particularly with regard to soot-NO_x trade-off behavior. The primary objective of the study is to examine whether the major potential of blending these two fuels is already largely exploited at low OME content, or if significant additional emission reduction potential can still be found with higher content blends, but still without the need to switch to pure OME operation. Furthermore, the fuel blend which is best suited for the realization of an ultra-low emission concept under the current technical conditions should be identified. In addition, three different injector designs were tested for operation on pure OME3-5, differing both in hydraulic flow and in the number of injection holes as well as their layout. The optimum configuration is evaluated with regard to emissions, normalized heat release and indicated efficiency.

Further stringent emission regulations of modern diesel engines call for a more precise prediction of NO_x emissions, thus enabling a better control of the exhaust-gas aftertreatment systems. A major part of the NO_x emissions is emitted before the light-off temperature of the selective catalytic reduction (SCR) catalyst is reached. Therefore a precise emissions prediction is necessary during the cold start phase of a diesel passenger car. Recent measurements show that NO_x emissions can be stored in the SCR catalysts during cold start. Furthermore a part of this stored NO_x can be reduced during the driving cycle.

This paper describes an empiric model predicting the NO_x storage behaviour during vehicle cold start. In a previous work the main influence parameters on the NO_x storage behaviour were investigated on a synthetic gas test bench. The knowledge gained from the previous research work defines the necessary input parameters for the NO_x storage model. These investigations showed that the NO_x storage effect strongly depends on the ammonia (NH₃-) level stored in the catalyst, exhaust-gas mass flow, the water adsorbed (H₂O) on the catalyst, and the temperature of the catalyst. The model was implemented for on-filter and flow-through SCR catalysts. There are two similar models, one for the close-coupled SCR system and the other one for the underfloor SCR system. Each NO_x storage model is split into an adsorption part and a desorption part. For both parts the pre-conditioning from the previous driving cycle is taken into account, which means that the catalyst state at the end of the last driving cycle initializes the model data for the current cycle, in consideration of the downtime between the two cycles. The desorption part calculates the NO_x conversion amount and defines the desorption mass flow of NO_x resulting from the NO_x storage effect. The developed NO_x storage model has been validated with roller dynamometer measurements and with real world driving cycles.

This article presents the setup and results of a recent subject study at the full-scale moving Stuttgart driving simulator. The study focusses on the passenger’s comfort during automated lane changes in a high-speed two-lane motorway scenario. The scenario contains different symmetric and asymmetric lane change trajectories, bends and road surface qualities. Each asymmetric trajectory is divided into two parts with different characteristics. The subjects input their subjective impression of comfort directly after each lane change on a tablet computer. The phase in which the vehicle leaves its previous lane and the phase in which the vehicle arrives at its target lane are rated individually. This enables a detailed effect analysis for the two characteristic parts of asymmetric lane change trajectory shapes. The evaluation method is able to determine subjective differences even at small objective changes. Result analysis verifies correlations between objective criteria describing the trajectory characteristics and the subjective comfort ratings. In addition, a curvature caused bias on the subjective ratings in bends is determined. The results motivate the curvature-dependent use of asymmetric lane change trajectories to improve comfort without reducing longitudinal velocity or increase lane change duration and thus maintaining traffic efficiency in terms of required traffic interspaces to cut in. The study data is further used for the development of a passengers’ comfort metric for automated driving functions.

The increasing CO₂ concentration in the atmosphere and the resulting climate change require an immediate and efficient reduction of anthropogenic carbon-dioxide emission. This target can be achieved by the usage of CO₂-neutral fuels even with current technologies (Schemme et al. in Int J Hydrogen Energy 45:5395–5414, 2020). Diesel engines in particular are amongst the most efficient prime movers. Using oxymethylene-dimethyl-ether (OME) it is possible to solve the hitherto existing Soot-NO_x-Trade-off. OME has bounded oxygen in the molecular chain. This reduces the formation of soot, but equally the calorific value. But in considerance of the physical and chemical properties of OME, it could be useful to optimize the standard diesel engine into an OME engine. As a result, single-cylinder tests were performed to obtain a detailed analysis of the differences between OME3-5 and commercially available DIN EN 590 Diesel. Based on the fact that OME has gravimetrically less than half the calorific value of diesel, twice the fuel mass must be injected for the same energy release in the combustion chamber. Therefore, at the beginning of the investigations, a variation of the injector flow rate was carried out by means of different nozzle hole diameters. The evaluation of the results included the fundamental differences in the combustion characteristics of both fuels and the determination of efficiency-increasing potentials in the conversion of OME3-5. Due to the lower ignition delay and the shorter combustion time of OME, potentials in the optimisation of the injection setting became apparent. Higher energy flows over the combustion chamber wall were noticeable in operation with OME. To get to the bottom of this, the single-cylinder investigations were supported by tests on the optically accessible high-pressure chamber and the single-cylinder transparent engine. The optical images showed a narrower cone angle and greater penetration depth of the OME injection jet compared to the diesel injection jet. This confirmed the results from the single-cylinder tests. This provides further potential in the design of the injector nozzle to compensate for these deficits. Overall, this work shows that operation with OME in a classic diesel engine is possible without any significant loss in efficiency and with little effort in the hardware. However, it is also possible to achieve more efficient use of the synthetic fuel with minor adjustments.

Due to the constantly increasing number of functions offered by a modern vehicle, the complexity of vehicle development is also increasing as a result. A first indication of this connection is provided by the number of ECUs (electronic control units) used in current development vehicles. Furthermore, each ECU also performs more functions and is not only electrically networked with the other ECUs, but also logically and functionally. On this basis, new cooperative functions are being developed, which are used for example for autonomous driving. In vehicle development, more and more test sequences (diagnostic scripts) are established for function testing of individual components, systems and cross-functional methods. Due to decentralization and the modular approach, modern development vehicles consist of different numbers of ECUs. The high number of ECUs in purpose and number poses a challenge for test creation and updating. The ECU software is also developed in cycles within the vehicle cycle. This results in a very high software variance. This variance leads to the fact that in the vehicle development with global test conditions works. Global test conditions at this point mean that more ECUs are included in the measurement procedure than are installed in the vehicle. The vehicle structure (control unit and its software version) is not known to the person performing the measurement. He relies on the fact that his ECUs are inside in the global measurement task. This means that the vehicle network architecture is uncertain, which can lead to errors during test execution. Since the ECUs that are actually installed in the vehicle are first determined during test execution, this results in a longer script runtime than would be necessary. To support the development engineer and prevent avoidable errors, the diagnostic system should configure itself as far as possible. This means that individually customized measurements for each vehicle should be calculated in the cloud and not the global measurement tasks. For a diagnostic system to be able to configure itself independently, the vehicle network structure must be determined in a first step. This can be done by a simple CAN measurement (measurementXY.asc). An AI is able to analyze this measurement and classify the occurring ECUs as well as CAN networks. For larger measuring devices with more than one CAN interface, the user who analyzes the measurement is interested in which CAN was connected. Here, the AI is suitable to determine the name of the network and the communicating ECUs based on the communication that runs over the bus. For this purpose, the AI classifies the number of communicating ECUs based on the time intervals at which messages are sent. In addition, the AI can be supported by a special diagnostic script (global.pattern) to determine the vehicle structure at the OBD (on-board diagnostics) interface with maximum accuracy. Three AI approaches are presented, all connected in series a