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.     

Optimal scheduling of the flexray static segment based on two-dimensional bin-packing algorithm

FlexRay is a reliable and hard real-time in-vehicle communication protocol that is strongly promoted by car manufacturers as the de facto standard in the automotive domain. The protocol offers both a time-triggered and an eventtriggered architecture. This paper focuses on the optimal scheduling of the time-triggered component of FlexRay known as the static (ST) segment using a two-dimensional bin-packing technique. To maximize the bandwidth utilization in the ST segment, a fast heuristic as well as an efficient integer linear programming approach are proposed. Our methods directly schedule signals into slots including frame packing, according to signal-based data scheduling and the slot/ cycle multiplexing mechanisms presented by the latest version of the FlexRay protocol. The benefits of our proposed methods are demonstrated by extensive experiments on synthetic and an automotive X-by-wire system case study. An additional test case is examined to emphasize the superior performance of the proposed approach relative to that of existing optimal scheduling approaches.     

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.     

Stress sensitivity analysis and optimization of automobile body frame consisting of rectangular tubes

At conceptual design stage, beam element is extensively used to create the frame structure of automobile body, which can not only archive the accurate stiffness but also reduce much computational cost. However, the stress definition of beam element is very complex so that the stress sensitivity and optimization are difficult to analytically derive and numerically program. This paper presents an solution to this problem and an application in the lightweight optimization design of automobile frame. Firstly, maximal Von Mises stress of rectangular tube is calculated by using the superposition of stress, which is together induced by the axial force, bending moments, torsional moment and shear force. Secondly, the sensitivity of Von Mises Stress with respect to size design variables: breadth, height and thickness are derived, respectively. Thirdly, an optimal criterion is constructed by Lagrangian multiplier method to solve the frame optimization with stress constraints. Lastly, numerical example of car frame proves that the proposed method can guarantee the stress of each beam element almost fully reaches at the yielding stress.     

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.     

Design of passive vehicle suspensions for maximal least damping ratio

This paper studies the use of the least damping ratio among system poles as a performance metric in passive vehicle suspensions. Methods are developed which allow optimal solutions to be computed in terms of non-dimensional quantities in a quarter-car vehicle model. Solutions are provided in graphical form for convenient use across vehicle types. Three suspension arrangements are studied: the standard suspension involving a parallel spring and damper and two further suspension arrangements involving an inerter. The key parameters for the optimal solutions are the ratios of unsprung mass to sprung mass and suspension static stiffness to tyre vertical stiffness. A discussion is provided of performance trends in terms of the key parameters. A comparison is made with the optimisation of ride comfort and tyre grip metrics for various vehicle types.     

Estimation of road profile variability from measured vehicle responses

When assessing the statistical variability of fatigue loads acting throughout the life of a vehicle, the question of the variability of road roughness naturally arises, as both quantities are strongly related. For car manufacturers, gathering information on the environment in which vehicles evolve is a long and costly but necessary process to adapt their products to durability requirements. In the present paper, a data processing algorithm is proposed in order to estimate the road profiles covered by a given vehicle, from the dynamic responses measured on this vehicle. The algorithm based on Kalman filtering theory aims at solving a so-called inverse problem, in a stochastic framework. It is validated using experimental data obtained from simulations and real measurements. The proposed method is subsequently applied to extract valuable statistical information on road roughness from an existing load characterisation campaign carried out by Renault within one of its markets.     

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.