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The proposed Euro 7 emission standard foresees that the emission behaviour of Euro 7 vehicles is monitored via an on-board monitoring (OBM) system. In Euro 7 vehicles, OBM systems will monitor the emissions of nitrogen oxides (NOX), ammonia (NH3) and particulate matter (PM) for every trip through a combination of measured and modelled data. Sensors employed to support on-board diagnostics (OBD) in current vehicles may be used to support OBM. According to the Euro 7 OBM concept presented in this paper, OBM will serve a dual purpose: the first is to warn the user of a vehicle about the need to perform repairs on the engine or the pollution control systems when these are needed. If these repairs are not performed in a timely manner, the OBM system will be able to ultimately prevent engine restart, akin to the existing low-reagent driver warning system in some compression ignition vehicles. The second purpose of OBM is to monitor the compliance of vehicle types with the emission limits.

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.

CO2 regulations on heavy-duty transport are introduced in essentially all markets within the next decade, in most cases in several phases of increasing stringency. To cope with these mandates, developers of engines and related equipment are aiming to break new ground in the fields of combustion, fuel and hardware technologies. In this work, a novel diesel fuel injector, Delphi’s DFI7, is utilized to experimentally investigate and compare the performance of ramped injection rates versus traditional square fueling profiles. The aim is specifically to shift the efficiency and NOx tradeoff to a more favorable position. The design of experiments methodology is used in the tests, along with statistical techniques to analyze the data. Results show that ramped and square rates - after optimization of fueling parameters - produce comparable gross indicated efficiencies.

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 article describes a NOx sensor based urea dosing control strategy for heavy-duty diesel aftertreatment systems using Selective Catalytic Reduction. The dosing control strategy comprises of a fast-response, model-based ammonia storage control system in combination with a long-timescale tailpipe-feedback module that adjusts the dosing quantity according to current aftertreatment conditions. This results in a control system that is robust to system disturbances such as biased NOx sensors and variations in AdBlue concentrations. The cross-sensitivity of the tailpipe NOx sensor to ammonia is handled by a novel, smart signal filter that can reliably identify the contributions of NOx and NH3 in the tailpipe sensor signal, without requiring an artificial perturbation of the dosing signal.

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.

The next generation off-road vehicles will see additional exhaust gas aftertreatment systems, ranging from DOC-SCR only to full DOC-DPF-SCR-AMOX systems. This will increase system complexity and development effort significantly. Emission requirements and the high number of vehicle configurations within the off-road industry will require a new process for development and validation. The introduced model-based approach using physical models of aftertreatment can reduce development effort and cost, improve performance robustness and help to identify performance issues early in the development process. A method to investigate and optimize a large matrix of variations by simulation is introduced. This can lead to a significant reduction in the number of required calibrations and can assist in the development of design specifications for the aftertreatment system. A case study for SCR calibration successfully demonstrates the potential of model-based development.

The problem of predicting the quality of weld is critical to manufacturing. A great deal of data is collected under multiple conditions to predict the quality. The data generated at Daimler Chrysler has been used to develop a model based on grammatical evolution. Grammatical Evolution Technique is based on Genetic Algorithms and generates rules from the data which fit the data. This paper describes the development of a software tool that enables the user to choose input variables such as the metal types of top and bottom layers and their thickness, intensity and speed of laser beam, to generate a three dimensional map showing weld quality. A 3D weld quality surface can be generated in response to any of the two input variables picked from the set of defining input parameters. This tool will enable the user to pick the right set of input conditions to get an optimal weld quality. The tool is developed in Matlab with Graphical User Interface for the ease of operation.

NVH targets for future vehicles are often defined by utilizing a competitive benchmarking vehicle in conjunction with an existing production and/or reference vehicle. Mode management of full vehicle modes is one of the most effective and significant NVH strategies to achieve such targets. NVH dynamic characteristics of a full vehicle can be assessed and quantified through experimental modal testing for determination of global body mode resonance frequency, damping property, and mode shape. Major body modes identified from full vehicle modal testing are primarily dominated by the vehicle's body-in-white structure. Therefore, an estimate of BIW modes from full vehicle modes becomes essential, when only full vehicle modes from experimental modal testing exist. Establishing BIW targets for future vehicles confines the fundamental NVH behavior of the full vehicle.

This paper describes the application of the modal compliance method to a complex structure such as a vehicle body in white, and the extension of the method from normal modes to the complex modes of a complete vehicle. In addition to the usual bending and torsion calculations, the paper also describes the application of the method to less usual tests such as second torsion, match-boxing and breathing. We also show how the method can be used to investigate the distribution of compliance throughout the structure.

Tailor welded steel blanks have long been applied in stamping of automotive parts such as door inner, b-pillar, rail, sill inner and liftgate inner, etc. However, there are few known tailor welded aluminum blanks in production. Traditional laser welding equipment simply does not have the capability to weld aluminum since aluminum has much higher reflectivity than steel. Welding quality is another issue since aluminum is highly susceptible to pin holes and undercut which leads to deterioration in formability. In addition, high amount of springback for aluminum panels can result in dimension control problem during assembly. A tailor-welded aluminum blank can help reducing dimension variability by reducing the need for assembly. In this paper, application of friction stir and plasma arc welded blanks on a liftgate inner will be discussed.

This paper identifies the difference in powertrain cooling system content levels using a nominal and a +3 Standard deviation maximum temperature design approach. Variation simulation analysis tools are used along with a 1-D cooling system performance model to predict resulting temperature distribution for different combinations of input variable populations. The analysis will show differential in powertrain cooling system content, mass, and impact to fuel economy for a nominal vs. +3 sigma design approach.

Brake judder, which is a low frequency excitation of the suspension and thus, the body structure during low-G braking, is mainly felt at the steering wheel and throughout the vehicle structure. Brake judder is a problem that costs manufacturers millions of dollars in warranty cost and undesirable trade offs. The magnitude of judder response depends not only on the brake torque variation, but also on the suspension design character-istics. This paper discusses the judder simulation process using ADAMS software to investigate the suspension design sensitivity to the first order brake judder performance. The paper recommends “tuning knobs” to suspension designers and vehicle development engineers to resolve issues in the design and development stages. Various suspension design varia-bles including geometry and compliances as well as brake related characteristics were investigated.

To mitigate head impact injuries of vehicle occupants in impact accidents, the FMVSS 201 requires padding of vehicle interior so that under the free-moving-head-form impact, the head injury criterion (HIC) is below the limit. More recently, pedestrian head impact on the vehicle bonnet has been a subject being studied and regulated as requirements to the automobile manufacturers. Over the years, the square wave has been considered as the best waveform for head impacts, although it is impractical to achieve. This paper revisits the head impact topic and challenges the optimality of aiming at the square waveform. It studies several different simple waveforms, with the objective to achieve minimal HIC or minimal crush space required in head-form impacts. With that it is found that many other waveforms can be more efficient and more practical than the square wave, especially for the pedestrian impact.

Transmission mounts are usually tested as an assembly and typically only translational stiffnesses are provided. The torsional stiffness of the assembly is traditionally estimated based on experience in load simulation and analysis. This paper presents a procedure to estimate the torsional stiffness of the transmission mount assembly by using the test data. The effects of the torsional stiffness on the simulation results are also discussed.

To meet 2010 emission targets, optimal SCR system performance is required. In addition, attention has to be paid to in-use compliance requirements. Closed-loop control seems an attractive option to meet the formulated goals. This study deals with the potential and limitations of closed-loop SCR control. High NOx conversion in combination with acceptable NH3 slip can be realized with an open-loop control strategy. However, closed-loop control is needed to make the SCR system robust for urea dosage inaccuracy, catalyst ageing and NOx engine-out variations. Then, the system meets conformity of production and in-use compliance norms. To demonstrate the potential of closed-loop SCR control, a NOx sensor based control strategy with cross-sensitivity compensation is compared with an adaptive surface coverage/NH3 slip control strategy and an open-loop strategy. The adaptive surface coverage/NH3 slip control strategy shows best performance over simulated ESC and ETC cycles.

In the development of several outside mirror designs for vehicles, a high frequency noise (whistling) phenomenon was experienced. First impression was that this might be due to another source on the vehicle (such as water management channels) or a cavity noise; however, upon further investigation the source was found to be the mirror housing. This “laminar whistle” is related to the separation of a laminar boundary layer near the trailing edges of the mirror housing. When there is a free stream impingement on the mirror housing, the boundary layer starts out as laminar, but as the boundary layer travels from the impingement point, distance, speed, and roughness combine to trigger the transition turbulent. However, when the transition is not complete, pressure fluctuations can cause rapidly changing flow patterns that sound like a whistle to the observer. Because the laminar boundary layer has very little energy, it does not allow the flow to stay attached on curved surfaces.

In embedded software world, development and testing are becoming far more complex with growing functionality and fail safe strategies. As a result of that, model-based software development is getting increasingly popular in capturing the functional requirements and auto generating the code from these validated models to avoid any functional deficiency. However, the complexity in the model may not be correctly interpreted by the code generation tool and may result to an incorrect code behavior. In this paper, a methodology has been proposed and implemented to validate the generated code against the models. Simulation test scripts are recorded in the modeling environment to generate the desired set of test inputs. These input scripts are designed to get complete transition and state exposure to maximize the functional coverage. With these test scripts, expected outputs are recorded for downstream validation in the simulation environment with mature models.

As the hybrid automotive market becomes quickly saturated with highly competitive products and vehicles, auto manufacturers struggle with business models and the combination of current manufacturing with next generation development. The hybrid development cooperation amongst General Motors, DaimlerChrysler, and BMW offers a new business model that promotes the advancement of the state of strong hybrid technology while maintaining the strong global leadership and competition.

Laser lap welding quality is a non-linear response based on a host of categorical and numeric material and process variables. This paper describes a Grammatical Evolution approach to the structure identification of the laser lap welding process and compares its performance with linear regression and a neuro-fuzzy inference system.