理解消费者对质量的定义

汽车产品的质量总是会受到巨大的关注。质量较差会导致财务成本的增加,这使得制造商把提升质量作为一项商业必要的手段。过去的数年中有无数方法和流程被用来减少浪费和消除缺陷 (比如6-Sigma法和TQM完全质量管理法)。我们并不缺少这样的衡量工具,来衡量因质量问题和返工而产生的负面经济效益。运用这些衡量工具能够理解质量对每辆车或者公司的盈利能力造成的影响,并且帮助公司取得显著的产品质     

Cycle-simulation turbulence modelling of IC engines

Numerical simulations of IC engines are of high interest for automotive engineers worldwide. The simulation models should be as fast as possible, low-computational effort and predictive tool. The correct prediction of turbulence level inside the combustion chamber of spark ignition engines is the most important factor influencing to the engine working cycle. This paper presents a development of the k-ε turbulence model applied to the commercial cycle-simulation software with the high emphasis on the intake part. The validation was performed on two engine geometries with the variation of engine speed and load comparing the cycle-simulation results of the turbulent kinetic energy and in-cylinder temperature with 3-D CFD results. In order to apply the cycle-simulation turbulence model for the simulation of entire engine map, the parameterization model of turbulence constants was proposed. The parameterized turbulence model was optimized using NLPQL optimization algorithm where the single set of turbulence model parameters for each engine was found. A good agreement of the turbulent kinetic energy during the expansion was achieved when the turbulence affects the flame front propagation and combustion rate as well.     

Real-time empirical NO<Subscript>x</Subscript> model based on In-cylinder pressure measurements for light-duty diesel engines

This paper proposes a real-time empirical model of NO_x emissions for diesel engines. The proposed model predicts the level of NO_x emissions using an empirical model developed based on the thermal NO formation mechanism, the extended Zeldovich mechanism. Since it is difficult to consider the exact physical NO formation phenomena in real-time applications, the proposed algorithm adapts the key factors of the NO formation mechanism from the extended Zeldovich mechanism: temperature of the burned gas, concentration of the gas species, and combustion duration where NO is generated. These factors are considered in a prediction model as four parameters: exhaust gas recirculation rate (EGR rate), crank angle location of 50 % of mass fraction burned (MFB50), exhaust lambda value, and combustion acceleration. The proposed prediction model is validated with various steady engine experiments that showed a high linear correlation with the NO_x emission measured by a NO_x sensor. Furthermore, it is also validated for transient experiments.     

Resource-aware integration of AUTOSAR-compliant ECUs with an empirical wcet prediction model

This paper presents an integration method of AUTOSAR-compliant ECUs which can evaluate resource constraints in an early-stage of development. There are three types of resources for an ECU (timing, memory, and interface) which should be carefully managed for successful ECU integration. The proposed method consists of three steps: measurement, prediction, and evaluation. In the first step, a method to measure resource factors for AUTOSAR-compliant software architecture is introduced. Based on the method, a worst-case execution cycle of a runnable, memory section usages of a software component, and interface of legacy ECUs can be obtained. In the second step, the obtained factors are quantitatively predicted according to the architectural designs of the integration ECU. In the case of the timing resource, the worst-case execution time of the integration ECU can be precisely predicted by a proposed empirical model. In the last step, the resource constraints such as CPU, memory, network utilizations can be evaluated with predicted resource factors before implementation. The proposed method was applied to the integration of an in-house engine management system composed of two ECUs. The method successfully provided quantitative measures to evaluate architectural designs of three different integration scenarios.     

Topological analysis of powertrains for refuse-collecting vehicles based on real routes–Part I: Hybrid hydraulic powertrain

In this two-part paper, a topological analysis of powertrains for refuse-collecting vehicles (RCVs) based on the simulation of different architectures (internal combustion engine, hybrid electric, and hybrid hydraulic) on real routes is proposed. In this first part, a characterization of a standard route is performed, analyzing the average power consumption and the most frequent working points of an internal combustion engine (ICE) in real routes. This information is used to define alternative powertrain architectures. A hybrid hydraulic powertrain architecture is proposed and modelled. The proposed powertrain model is executed using two different control algorithms, with and without predictive strategies, with data obtained from real routes. A calculation engine (an algorithm which runs the vehicle models on real routes), is presented and used for simulations. This calculation engine has been specifically designed to analyze if the different alternative powertrain delivers the same performance of the original ICE. Finally, the overall performance of the different architectures and control strategies are summarized into a fuel and energy consumption table, which will be used in the second part of this paper to compare with the different architectures based on hybrid electric powertrain. The overall performance of the different architectures indicates that the use of a hybrid hydraulic powertrain with simple control laws can reduce the fuel consumption up to a 14 %.     

Rule-based control of a semi-active suspension for minimal sprung mass acceleration: design and measurement

In this paper, a rule-based controller is developed for the control of a semi-active suspension to achieve minimal vertical acceleration. The rules are derived from the results obtained with a model predictive controller. It is shown that a rule-based controller can be derived that mimics the results of the model predictive controller and minimises vertical acceleration. Besides this, measurements on a test vehicle show that the developed rule-based controller achieves a real-world reduction of the vertical acceleration, which is in agreement with the simulations.     

Prediction of the dimensional deformation of the addendum and dedendum after the warm shrink fitting process using a correction coefficient

The warm shrink fitting process is generally used to assemble automobile transmission parts (shafts/gears). However, this process causes a deformation in the addendum and dedendum of the gear depending on the fitting interference and gear profile, and this deformation causes additional noise and vibration between the gears. To address these problems, the warm shrink fitting process is analyzed by considering the error in the dimensional deformation of the addendum and dedendum found when comparing the results of a theoretical analysis and finite element analysis (FEA). A correction coefficient that reduces this error is derived through an analysis of the difference in the cross-sectional area between the shapes used for the theoretical analysis and that of the actual gear, and a closed-form equation to predict the dimensional deformation of the addendum and dedendum is proposed. The FEA method is proposed to analyze the thermal-structural-thermal coupled field analysis of the warm shrink fitting process (heating-fitting-cooling process). To verify the closed-form equation using the correction coefficient, measurements are made of actual helical gears used in automobile transmissions. The results are in good agreement with those given by the closed-form equation.     

Major sources of hydrocarbon emissions in a premixed charge compression ignition engine

Although premixed charge compression ignition (PCCI) combustion engines are praised for potentially high efficiency and clean exhaust, experimental engines built to date emit more hydrocarbons (HCs) and carbon monoxide (CO) than the conventional machines. These compounds are not only strictly controlled components of the exhaust gas of road vehicles but are also an energy loss indicator. The prime objective of this study was to investigate the major sources of the HCs formed in the combustion chamber of an experimental PCCI engine in order to suggest some effective technologies for HC reduction. In this study, to explore the dominant sources of HC emissions in both operation modes, a single cylinder engine was prepared such that it could operate using either conventional diesel combustion or PCCI combustion. Specifically, the contributions of the top-ring crevice volume in the combustion chamber and the bulk quenching of the lean mixture were investigated. To understand the influence of the shape and magnitude of the crevice on HC emissions, the engine was operated with 12 specially prepared pistons with different top-ring crevices installed one after another. The engine emitted proportionally more HCs as the depth of the crevice increased as long as the width remained narrower than the prevailing quench distance. The top-ring-crevice-originated exhaust HCs comprised approximately 31% of the total HC emissions in the baseline condition. In a series of tests to estimate the effects of bulk quench on exhaust HC emissions, intake air was heated from 300K to 400K in steps of 25K. With the intake air heated, HC and CO emissions decreased with a gradually diminishing rate to zero at 375K. In conclusion, the most dominant sources of HC emissions in PCCI engines were the crevice volumes in the combustion chamber and the bulk quenching of the lean mixtures. The key methods for reducing HC emissions in PCCI engines are minimizing crevice volume in the combustion chamber and maximizing intake air temperature allowed based on the permissible NOx level.     

High-strain-rate fracture of adhesively bonded composite joints in DCB and TDCB specimens

Double-cantilever beam (DCB) and tapered double-cantilever beam (TDCB) specimens are the test configurations most commonly used to measure the fracture toughness of composites and adhesive joints. Strain rates of 1 to 18.47 m/s were applied to the test specimens via high-speed hydraulic test equipment. Because the fracture occurs through the adhesively bonded joints and the cracks grow rapidly, the crack length and beam displacement were recorded by a high-speed camera. An energy range from 0 to 10 J was often observed in the high-strain-rate fracture experiments for nonlinear plastic behavior of the dynamically loaded adhesively bonded DCB and TDCB specimens. The range of energy release rates (fracture energy) for TDCB specimen was 2 to 3 times higher than that of a DCB specimen for all high strain rates. The fracture energy of automotive adhesive joints can be estimated using the experimental results in this study for the fracture toughness (G_IC) under high rates of loading. The crack grows as the applied fracture energy exceeds the value of the critical energy release rate (G_IC) at the crack tip. The energy release rate was calculated using the fracture mechanics formula. The key fracture mechanics parameter, the fracture energy GIC, was ascertained as a function of the test rate and can be used to assess and model the overall joint performance.     

Policy challenges of increasing automation in driving

The convergence of information and communication technologies (ICT) with automotive technologies has already resulted in automation features in road vehicles and this trend is expected to continue in the future owing to consumer demand, dropping costs of components, and improved reliability. While the automation features that have taken place so far are mainly in the form of information and driver warning technologies (classified as level I pre-2010), future developments in the medium term (level II 2010–2025) are expected to exhibit connected cognitive vehicle features and encompass increasing degree of automation in the form of advanced driver assistance systems. Although autonomous vehicles have been developed for research purposes and are being tested in controlled driving missions, the autonomous driving case is only a long term (level III 2025 +) scenario. This paper contributes knowledge on technological forecasts regarding automation, policy challenges for each level of technology development and application context, and the essential instrument of cost-effectiveness for policy analysis which enables policy decisions on the automation systems to be assessed in a consistent and balanced manner. The cost of a system per vehicle is viewed against its effectiveness in meeting policy objectives of improving safety, efficiency, mobility, convenience and reducing environmental effects. Example applications are provided that illustrate the contribution of the methodology in providing information for supporting policy decisions. Given the uncertainties in system costs as well as effectiveness, the tool for assessing policies for future generation features probabilistic and utility-theoretic analysis capability. The policy issues defined and the assessment framework enable the resolution of policy challenges while allowing worthy innovative automation in driving to enhance future road transportation.