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2-step variable valve actuation using early-intake valve closing is a strategy for high fuel economy on spark-ignited gasoline engines. Two discrete valve-lift profiles are used with continuously variable cam phasing. 2-step VVA systems are attractive because of their low cost/benefit, relative simplicity, and ease-of-packaging on new and existing engines. A 2-step VVA system was designed and integrated on a 4-valve-per-cylinder 4.2L line-6 engine. Simulation tools were used to develop valve lift profiles for high fuel economy and low NOx emissions. The intake lift profiles had equal lift for both valves and were designed for high airflow & residual capacity in order to minimize valvetrain switching during the EPA drive cycle. It was determined that an enhanced combustion system was needed to maximize fuel economy benefit with the selected valve lift profiles. A flow-efficient chamber mask was developed to increase in-cylinder tumble motion and combustion rates.

During the production controller and software development process, one critical step is the controller and software verification. There are various ways to perform this verification. One of the commonly used methods is to utilize an HIL (hardware-in-the-loop) test bench to emulate powertrain hardware for development and validation of powertrain controllers and software. A key piece of an HIL bench is the plant dynamics model used to emulate the external environment of a modern controller, such as engine (ECM), transmission (TCM) or powertrain controller (PCM), so that the algorithms and their software implementation can be exercised to confirm the desired results. This paper presents a 6-speed automatic transmission plant dynamics model development for hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The modeling method, model validation, and application in an HIL test environment are described in details.

This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software, with a focus on a closed-loop vehicle drive-train model incorporating a detailed automatic transmission plant dynamics model developed for certain applications. Specifically, this paper presents the closed-loop integration of a 6-speed automatic transmission model developed for our HIL transmission controller and algorithm test bench (Opal-RT TestDrive based). The model validation, integration and its application in an HIL test environment are described in details.

In this paper, a comparative study of the production applications of hybrid electric powertrains is presented. Vehicles studied include the Toyota Prius, Honda Insight, Toyota Estima, Toyota Crown, Honda Civic Hybrid, and Nissan Tino. The upcoming Ford Escape Hybrid and General Motors Parallel Hybrid Truck (PHT) will also be included, although advance information is limited. The goal of this paper is to look at what hybrid drivetrain architectures have actually been selected for production and what are the underlying details of these drivetrains. Since hybridizing a powertrain involves significant changes, the powertrain architectures are presented in diagram form, with analysis as to the similarities and advantages represented in these architectures. The specific hybrid functions used to save fuel are discussed. Peak power-to-weight ratio and degree of hybridization are plotted for the vehicles. System voltage versus electric power level are also plotted and analyzed.

Production software validation is critical during software development, allowing potential quality issues that could occur in the field to be minimized. By developing automated and repeatable software test methods, test cases can be created to validate targeted areas of the control software for confirmation of the expected results from software release to release. This is especially important when algorithm/software development timing is aggressive and the management of development activities in a global work environment requires high quality, and timely test results. This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The powertrain model used within the HIL consists of an engine model and a detailed automatic transmission dynamics model. The model runs in an OPAL-RT TestDrive based HIL system.

A key quantity for use in engine control is the exhaust manifold pressure. For production applications it is an important component in the calculation of the engine volumetric efficiency, as well as EGR flow and residual fraction. For cost reasons, however, it is preferable to not have to measure the exhaust manifold pressure for production applications. For that reason, it is advantageous to develop a model for estimating the exhaust manifold pressure in production application software that is small, accurate, and simple to calibrate. In this paper, a mean-value model for calculating the exhaust manifold pressure is derived from the compressible flow equation, treating the exhaust system as a fixed-geometry restriction between the exhaust manifold and the outlet of the tailpipe. Validation data from production applications is presented.

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 start algorithm that is able to control the air/fuel ratio (AFR) during the cranking phase and immediately hereafter, where the ordinary λ-control is not yet enabled. The control is based on the ion sense principle, which means that a current through the spark plug is measured directly after the spark has disappeared. This current is a measure for the temperature and therefore of the combustion in the cylinder. This is an excellent way to start a CNG (Compressed Natural Gas) engine with unknown gas qualities. A typical example of application is when the vehicle is almost out of fuel and is refueled at a motel stop. The small amount of old fuel that is left in the system will mix with the new fuel resulting in an unknown fuel quality. The control system shall then be able to start the engine directly or after an accommodation over night. During the last condition, the oxygen sensor is still cold and thus not able to correct for fuel quality changes.

The need for improved emissions control in lean exhaust to meet tightening, world-wide NOx emissions standards has led to the development of selective catalytic reduction of NOx with ammonia as a major technology for emissions control. Current systems are being designed to use a solution of urea (32.5 wt %) dissolved in water or Diesel Exhaust Fluid (DEF) as the ammonia source. While DEF or AdBlue® is widely used as a source of ammonia, it has a number of issues at low temperatures, including freezing below −12 °C, solid deposit formation in the exhaust, and difficulties in dosing at exhaust temperatures below 200 °C. Additionally creating a uniform ammonia concentration can be problematic, complicating exhaust packaging and usually requiring a discrete mixer.

The introduction of a new comfortable car seat or interior is a time consuming and costly process for car and seat manufacturers. The application of numerical models of human and seat could facilitate this process. Vertical vibrations and seat pressure distributions are two objective parameters that have been related to the subjective feeling of (dis)comfort that can be predicted by numerical tools. In this paper, human models suitable for prediction of human behaviour in vertical vibrations and seat pressure distributions are applied in a seat sensitivity study. The objective of this paper is to evaluate the applicability of the human models as design tools for car and seat developers in an early stage of the design process. The sensitivity of the output of the models for variations in seat characteristics for seat developers in the design process of a new comfortable car seat has been studied.

The paper describes the development of a vehicle stability indicator based on the correlation between various current vehicle chassis sensors such as hand wheel angle, yaw rate and lateral acceleration. In general, there is a correlation between various pairs of sensor signals when the vehicle operation is linear and stable and a lack of correlation when the vehicle is becoming unstable or operating in a nonlinear region. The paper outlines one potential embodiment of the technology that makes use of the Mahalanobis distance metric to assess the degree of correlation among the sensor signals. With this approach a single scalar metric provides an accurate indication of vehicle stability.

Virtual testing has grown to be an efficient tool in vehicle passive safety design. Most simulations currently are deterministic. Since the responses observed in real-life and standardized tests are greatly affected by scatter, a stochastic approach should be adopted in order to improve the predictability of the numerical responses with respect to the experimental data. In addition, an objective judgement of the performance of numerical models with respect to experimental data is necessary in order to improve the reliability of virtual testing. In the European VITES & ADVANCE project the software tool Adviser was developed in order to fulfil these two requirements. With Adviser, stochastic simulations can be performed and the quality of the numerical responses with respect to the experimental can be objectively rated using pre-defined and user-defined objective correlation criteria. The software Adviser was used to develop a stochastic HybridIII 50th% Madymo numerical model.

Among the performance concerns in brake design, drag and fluid displacement are getting more attention in the requirement definition. High drag not only affects fuel efficiency and lining life, it is also a contributing factor to rotor thickness variation and brake pulsation. In this paper, a system approach to drag performance of a disc brake caliper is presented. A one-dimensional simulation model, which considers all the significant factors, including lining stiffness and hysteresis, housing stiffness, seal/groove characteristic, and stick-slide behavior between the seal and piston, is developed to capture the interactive impact of each parameter to caliper drag performance. The system model is validated with experimental measurements for caliper fluid displacement and piston retraction. A parameter study is then conducted to investigate the component interactive impact to the drag performance.

In a competitive engineering business world, there is a constant demand to meet stringent emissions and on board diagnostic (OBD) regulations in a cost-effective manner. Engineers are tasked with the responsibility to innovate and design solutions around cost-cutting measures that involve reducing bill of material costs on the printed circuit board (PCB). Varied features in commercial application specific integrated circuits (ASIC) devices makes it more challenging to create consistent engineering design methods to provide critical inputs for controls and diagnostic strategies. In addition, continuous evolution of the emissions and OBD regulations in the different markets make it challenging for ASIC design manufacturers to evolve their hardware designs quickly. One such input is soak time. Soak time is typically defined as the amount of time the engine has been turned off. Emission controls and OBD algorithms use soak time to enable cold and hot start processing strategies.

Close-coupled or manifold catalysts have been extensively employed to reduce emissions during cold start by achieving quick catalyst light-off. These catalysts must have good thermal durability, high intrinsic light-off activity and high HC/CO/NOx conversions at high temperature and flow conditions. A number of studies have been dedicated to engine control, manifold design and converter optimization to reduce cold start emissions. The current paper focuses on the effect of catalyst design parameters and their performance response to different engine operating conditions. Key design parameters such as catalyst formulation (CeO2 vs. non CeO2), precious metal loading and composition (Pd vs. Pd/Rh), washcoat loading, catalyst thermal mass, substrate properties and key application (in use) parameters such as catalyst aging, exhaust A/F ratio, A/F ratio modulation, exhaust temperature, temperature rise rate and exhaust flow rate were studied on engine dynamometers in a systematic manner.

Nowadays virtual testing and prototyping are generally accepted methods in crash safety research and design studies. Validated numerical crash dummy models are necessary tools in these methods. Computer models need to be robust, accurate and CPU efficient, where the balance between accuracy and efficiency is depending on the nature of the study performed. This paper presents the application of advanced multibody-modelling techniques, in order to generate crash dummy models that are accurate as well as CPU efficient. Two techniques, deformable body modelling and arbitrary surface modelling, are combined. Their application is presented by means of an example model: the Hybrid III 50th percentile thorax. The method for generating the model is explained, after which the accuracy and efficiency of the model is illustrated by presenting some simulation results.

Selective Catalytic Reduction (SCR) is the dominant solution for meeting future NOx reduction regulations for heavy-duty diesel powertrains. SCR systems benefit from closed-loop control if an appropriate exhaust gas sensor were available. An ammonia sensor has recently been developed for use as a feedback element in closed-loop control of urea dosing in a diesel SCR aftertreatment system. Closed-loop control of SCR dosing enables the SCR system to be robust against disturbances and to meet conformity of production (COP) and in-use compliance norms. The ammonia sensor is based on a non-equilibrium electrochemical principle and outputs emf signals. The sensor performs well when tested in a diesel engine exhaust environment and has minimum cross interference with CO, HC, NO, NO2, SO2, H2O and O2. Previous work, done in a simulation environment, demonstrated that an ammonia sensor provides the optimal feedback for urea dosing control algorithms in closed-loop SCR systems.

In recent years, gasoline direct injection (GDi) engines have been popular due to their inherent potential for reduction of exhaust emissions and fuel consumption to meet stringent EPA standards. These engines require high-pressure fuel injection in order to improve the atomization process and accelerate mixture preparation. The high-pressure fuel pump is an essential component in the GDi system. Therefore, understanding the flow characteristics of this device and its associated behavior is critical for improving the performance of this category of engines. In this paper, the fluid flow characteristics in a high-pressure single-piston pump for use in GDi engines are analyzed using 1-D LMS Imagine.Lab AMESim system and 3-D Ansys Fluent computational fluid dynamics (CFD) models. The flow rate of the fuel pump under various cam speeds has been examined along with characteristics of the pump's control valve.

The information provided by the in-cylinder pressure signal is of great importance for modern engine management systems. The obtained information is implemented to improve the control and diagnostics of the combustion process in order to meet the stringent emission regulations and to improve vehicle reliability and drivability. The work presented in this paper covers the experimental study and proposes a comprehensive and practical solution for the estimation of the in-cylinder pressure from the crankshaft speed fluctuation. Also, the paper emphasizes the feasibility and practicality aspects of the estimation techniques, for the real-time online application. In this study an engine dynamics model based estimation method is proposed. A discrete-time transformed form of a rigid-body crankshaft dynamics model is constructed based on the kinetic energy theorem, as the basis expression for total torque estimation.

An integrated optimization system has been developed to combine optimization algorithms with Finite Element Analysis for airbag design. A number of industry standard software packages are employed to work in coherence to complete the optimization procedure automatically with minimal user intervention. The system can be easily tailored to fit multiple performance requirements and various design constraints for different airbag systems. Compared with the commonly used Design of Experiment (DOE) method, time and computer resources requirements are greatly curtailed. The integrated optimization system was successfully used in single-chamber and dual-chamber airbag optimizations. The results proved the effectiveness of the system and demonstrated its capability in product design.