Trigger algorithm of vehicle automatic crash notification system

The Automatic Crash Notification (ACN) system is an effective technology to decrease the crash response time, improve the level of post-accident rescue and alleviate the severity of injuries. To realize this system, a vehicle terminal is developed. And based on a moving window integral algorithm, the trigger algorithm of ACN system is designed. By comparing the effect of different window widths on the trigger algorithm, we select the window width of the moving window integral algorithm as 8 ms. After system is triggered, different notify types was determined according to the change of velocity in the moving window. A sled impact simulation test shows that the impact can be identified rapidly and also the notify types can be judged by the trigger algorithm. A vehicle road test proves that the ACN system has no false trigger cases. The outcomes of this study support identifications of accidents and crash severities for both occupants and emergency centers.     

Application of a modified thermostatic control strategy to parallel mild HEV for improving fuel economy in urban driving conditions

A modified thermostatic control strategy is applied to the powertrain control of a parallel mild hybrid electric vehicle (HEV) to improve fuel economy. This strategy can improve the fuel economy of a parallel mild HEV by operating internal combustion engine (ICE) in a high-efficiency region. Thus, in this study, experiments of a parallel mild HEV were conducted to analyze the characteristics of the hybrid electric powertrain and a numerical model is developed for the vehicle. Based on the results, the thermostatic control strategy was modified and applied to the vehicle model. Also, battery protection logic by using electrochemical battery model is applied because the active usage of battery by thermostatic control strategy can damage the battery. The simulation results of the vehicle under urban driving conditions show that the thermostatic control strategy can improve the vehicle’s fuel economy by 3.7 % compared with that of the conventional strategy. The results also suggest that the trade-off between the fuel economy improvement by efficient ICE operation and the battery life reduction by active battery usage should be carefully investigated when a thermostatic control strategy is applied to a parallel mild HEV.     

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.     

Flamelet combustion model for stratified EGR distribution in a diesel engine

Numerous research has been devoted to finding a method to simultaneously reduce NOx and soot emissions from diesel engines. In-cylinder EGR stratification is a technique that simultaneously reduces NOx and soot using a nonuniform EGR distribution in the combustion chamber. To study the potential of in-cylinder EGR stratification, a new combustion model is required that considers the non-uniform EGR distribution and the chemical kinetics. In this study, a new combustion model, the Flamelet for Stratified EGR (FSE) model, was developed to consider the non-uniform in-cylinder gas distribution based on chemical kinetics. The concept of the FSE model is based on using multiple flamelets with the multizone concept. To describe the non-uniform gas distribution, the combustion chamber is divided into several zones by oxygen concentration at the start of injection. Then, the flamelet equations are solved at the boundary of each zone. The final species mass fraction of each cell is calculated using linear interpolation between two results from the boundaries. In this paper, the FSE model was validated under in-cylinder EGR stratification conditions, and then, the potential of in-cylinder EGR stratification was studied by using the FSE model. The effect of in-cylinder EGR stratification was verified under various injection timing, engine speed, and road conditions with optimized engine geometries. The results shows simultaneous NOx and soot reductions under the stratified EGR condition.     

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.     

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.     

Research on control strategy for differential steering system based on H mixed sensitivity

The differential steering system (DSS) of electric wheel vehicle gets rid of the restrictions of traditional steering system completely. As an ideal steering technology, it not only realizes the perfect combination of the road feel and the steering portability, but also realizes the harmony and unification between the steering maneuverability and safety. The structure and basic theory of the DSS of electric wheel vehicle are discussed in this paper. Based on these, the dynamic model of the steering system is built. Considering of the uncertainties and disturbances existing in the model, the H_∞ mixed sensitivity control theory is applied to achieve better tracking performance and road feel in the process of steering. Then, a H_∞ mixed sensitivity controller is designed to restrain the effect of the road disturbance and model uncertainties. The simulation results indicate that the DSS with the designed controller can effectively restrain the effect of noises and disturbances caused by random motivation from road, torque sensor measurement and model parameter uncertainty, and enable the driver to obtain satisfactory road feel.     

3D brush model to predict longitudinal tyre characteristics

A 3D tyre brush model, which aims to predict the longitudinal tyre characteristic under steady-state conditions by modelling the occurring physical effects in the tyre–road contact patch, is presented. The model includes an analytical method to describe the tyre footprint geometry, the pressure distribution, the slip due to the lateral tyre contour, the slip due to braking or traction and the longitudinal as well as the lateral shear stresses on a flattened tyre. The presented development tool offers a method to investigate different rubber friction data (caused by different tread compounds and/or surface textures) and to analyse its influence on longitudinal tyre characteristics. The tyre design is fixed (same casing, dimension and pattern). The results include the shear stresses as well as the different sliding velocities in the contact patch for different slip conditions. The model was developed for a standard summer pattern design and a standard tyre dimension (205/55R16). It can also be adapted to other tread designs and tyre dimensions. To offer a good comparability between model results and test bench measurements, the surface curvature of an internal test rig is considered.     

Choice of parking: Stated preference approach

Over recent years, parking policy has become a key element of transport policy in many countries. Parking policy measures can affect many different dimensions of travel behaviour but are likely to be most significant in terms of travellers' choice of parking type and location. This dimension of travel choice has, to date, received comparatively little attention, yet is of vital importance if we are to properly understand and predict the effects of parking policy measures.This paper presents two studies addressing this issue carried out in the United Kingdom and Germany. Both studies used a stated preference approach in order to collect disaggregate data on travellers responses to changes in parking attributes and used these data to build simple logit models of parking type choice. The studies were designed in order to allow comparable choice models to be estimated from the two datasets. The results obtained strongly indicate the need to separately identify the costs associated with different components of the parking activity (e.g., general in-vehicle time, parking search time, egress time) and also point to the existence of significant differences in the relative valuation of these components across different journey purposes. Where possible, the results of the choice modelling exercises are also compared with existing revealed and stated preference results and are found to be generally in line with prior expectations.