Continuous remote emissions monitoring – the lynchpin for air quality management

Diesel particulate matter (DPM), in particular, has been likened in a somewhat inflammatory manner to be the ‘next asbestos’. From the business change perspective, there are three areas holding the industry back from fully engaging with the issue: 1. There is no real feedback loop in any operational sense to assess the impact of investment or application of controls to manage diesel emissions. 2. DPM are getting ever smaller and more numerous, but there is no practical way of measuring them to regulate them in the field. Mass, the current basis of regulation, is becoming less and less relevant. 3. Diesel emissions management is generally wholly viewed as a cost, yet there are significant areas of benefit available from good management. This paper discusses a feedback approach to address these three areas to move the industry forward. The six main areas of benefit from providing a feedback loop by continuously monitoring diesel emissions have been identified: 1. Condition-based maintenance. Emissions change instantaneously if engine condition changes. 2. Operator performance. An operator can use a lot more fuel for little incremental work output through poor technique or discipline. 3. Vehicle utilisation. Operating hours achieved and ratios of idling to under power affect the proportion of emissions produced with no economic value. 4. Fuel efficiency. This allows visibility into other contributing configuration and environmental factors for the vehicle. 5. Emission rates. This allows scope to directly address the required ratio of ventilation to diesel emissions. 6. Total carbon emissions - for NGER-type reporting requirements, calculating the emissions individually from each vehicle rather than just reporting on fuel delivered to a site.

Ignition delay of bio-fuels in a common-rail compression ignition engine

The utility of a novel technique for determining the ignition delay in a compression ignition engine has been shown. This method utilises statistical modelling in the Bayesian paradigm to accurately resolve the start of combustion from a band-pass in-cylinder pressure signal. Applied to neat diesel and six biofuels, including four fractionations of palm oil of varying carbon chain length and degree of unsaturation, the relationships between ignition delay, cetane number and oxygen content have been explored. It is noted that the expected negative relationship between ignition delay and cetane number held, as did the positive relationship between ignition delay and oxygen content. The degree of unsaturation was also identified as a potential factor influencing the ignition delay.

Stiffness-damping matching method of an ECAS system based on LQG control

A novel method of matching stiffness and continuous variable damping of an ECAS (electronically controlled air suspension) based on LQG (linear quadratic Gaussian) control was proposed to simultaneously improve the road-friendliness and ride comfort of a two-axle school bus. Taking account of the suspension nonlinearities and target-height-dependent variation in suspension characteristics, a stiffness model of the ECAS mounted on the drive axle of the bus was developed based on thermodynamics and the key parameters were obtained through field tests. By determining the proper range of the target height for the ECAS of the fully-loaded bus based on the design requirements of vehicle body bounce frequency, the control algorithm of the target suspension height (i.e., stiffness) was derived according to driving speed and road roughness. Taking account of the nonlinearities of a continuous variable semi-active damper, the damping force was obtained through the subtraction of the air spring force from the optimum integrated suspension force, which was calculated based on LQG control. Finally, a GA (genetic algorithm)-based matching method between stepped variable damping and stiffness was employed as a benchmark to evaluate the effectiveness of the LQG-based matching method. Simulation results indicate that compared with the GA-based matching method, both dynamic tire force and vehicle body vertical acceleration responses are markedly reduced around the vehicle body bounce frequency employing the LQG-based matching method, with peak values of the dynamic tire force PSD (power spectral density) decreased by 73.6%, 60.8% and 71.9% in the three cases, and corresponding reduction are 71.3%, 59.4% and 68.2% for the vehicle body vertical acceleration. A strong robustness to variation of driving speed and road roughness is also observed for the LQG-based matching method.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Effect of joint mechanism on vehicle redirectional capability of water-filled road safety barrier systems

Portable water-filled barriers (PWFBs) are roadside appurtenances that prevent vehicles from penetrating into temporary construction zones on roadways. PWFBs are required to satisfy the strict regulations for vehicle re-direction in tests. However, many of the current PWFBs fail to re-direct the vehicle at high speeds due to the inability of the joints to provide appropriate stiffness. The joint mechanism hence plays a crucial role in the performance of a PWFB system at high speed impacts. This paper investigates the desired features of the joint mechanism in a PWFB system that can re-direct vehicles at high speeds, while limiting the lateral displacement to acceptable limits. A rectangular “wall” representative of a 30 m long barrier system was modeled and a novel method of joining adjacent road barriers was introduced through appropriate pin-joint connections. The impact response of the barrier “wall” and the vehicle was obtained and the results show that a rotational stiffness of 3000 kNm/rad at the joints seems to provide the desired features of the PWFB system to re-direct impacting vehicles and restrict the lateral deflection. These research findings will be useful to safety engineers and road barrier designers in developing a new generation of PWFBs for increased road safety.

Seat Comfort. M4-M6.

Hardness is defined as the resistance and load bearing capability of an item. Seat hardness is an important factor in seat comfort as it impacts on a number of variables including seat postural stability, postural control, pressure comfort as a result of tissue deformation, and occupant vibration. The development of the test rig further on described in this report will enable Futuris Automotive to develop their current comfort testing procedures and thus increase the comfort of their automotive seats. The test rig consists of a buttock indenter, which produces a controlled application of a load to a seat cushion with measured displacement via a linear indenter. In parallel with the physical property presented, an analytic (software) finite element tool was developed to simulate seat pressure in an ANSYS Workbench V13 environment. This report also details the procedure required for Futuris to accurately and precisely measure cushion hardness which will enhance their comfort testing procedures, product development and target settings. The report is divided into three main sections: 1 Test equipment specification (M4) - A detailed description of the process used to build the seat cushion indenter and a description of the indenter mechanical structure and electrical functionality (chapter 2). 2 Analytic tool specification (M5) – A detailed description of the CAE seat and indenter software tool, developed as a finite element model (FEM) under ANSYS Workbench V13 to simulate indentation of a physical seat cushion similar to the hardware tool (chapter 3). 3 Product Development and Comfort Design Procedure (M6) - The cushion hardness testing procedure to be used with the physical indenter. This milestone is partially incomplete, as it covers a description of the test procedure to be applied, however not the operating system (control software) required to operate the physical property (chapter 4). Although outside the scope of this project, this report also details the testing procedures required to measure overall seatback hardness.

Determinants of second row passenger comfort

China is becoming an increasingly important automotive market. Customer’s vehicle usage, preferences and requirements differ from traditional western markets in a number of aspects – rear seat usage rates are higher, vehicles are used for business purposes as well as for private transport and rear seat usage is generally more important to Chinese customers compared to their western counterparts. The purpose of this project is to dimension and investigate these differences from an ergonomics perspective and use these results to guide the design of future products. The focus for this project will be specific to vehicles in the CD segment. More specifically, this project focuses on the second row ‘ambience’. Ambience refers to the global feeling perceived by second row passengers, and the main factors contributing to ambience are: ingress and egress comfort, seat comfort, roominess, and ease of use of the controls. In order to investigate the aforementioned parameters, an experimental study has been conducted in Shanghai, China. This experiment involved 80 healthy Chinese CD- and D-car customers. These subjects were asked to evaluate different features present in the second row environment of three different cars: A Ford Mondeo, Toyota Camry and Mercedes S-class. Various data has been collected during this experiment: First, the anthropometric dimensions of the subjects have been measured. The subjects were also asked to fill a questionnaire about demographics, their own car usage, and their perception of a various number of features present in the three tested cars. A great amount of technical data was also collected. The first part of this report presents the results given by the questionnaires. It includes Chinese demographics, vehicle usage habits, and the subjective perception of the features present in the tested cars. It also presents the results of the anthropometric measurements. This gives a first insight into Chinese customers’ habits and preferences. The second part deals with the technical data recorded during the experiment: second row seat adjustment ranges, roominess, optimal location of controls, and pressure mapping analysis. Analysis of technical data allows a deeper understanding of the factors contributing to comfort and ambience perception. Using the technical data together with the comfort ratings given by the subjects in the questionnaire, recommendations on several design parameters were provided. Finally, an experimental study of car ingress-egress has been conducted in a University laboratory controlled environment. During this study, the ingress and egress motion of 20 customers from Chinese origin was recorded using a motion capture system. The last part of this report presents the protocol and data processing that led to building an ingress-egress motion database that was provided to Ford.

Seat Comfort. M2-M3

This (seat) attribute target list and Design for Comfort taxonomy report is based on the literature review report (C3-21, Milestone 1), which specified different areas (factors) with specific influence on automotive seat comfort. The attribute target list summarizes seat factors established in the literature review (Figure 1) and subsumes detailed attributes derived from the literature findings within these factors/classes. The attribute target list (Milestone 2) then provides the basis for the “Design for Comfort” taxonomy (Milestone 3) and helps the project develop target settings (values) that will be measured during the testing phase of the C3-21 project. The attribute target list will become the core technical description of seat attributes, to be incorporated into the final comfort procedure that will be developed. The Attribute Target List and Design for Comfort Taxonomy complete the target definition process. They specify the context, markets and application (vehicle classes) for seat development. As multiple markets are addressed, the target setting requires flexibility of variables to accommodate the selected customer range. These ranges will be consecutively filled with data in forthcoming studies. The taxonomy includes how and where the targets are derived, reference points and standards, engineering and subjective data from previous studies as well as literature findings. The comfort parameters are ranked to identify which targets, variables or metrics have the biggest influence on comfort. Comfort areas included are seat kinematics (adjustability), seat geometry and pressure distribution (static comfort), seat thermal behavior and noise/vibration transmissibility (cruise comfort) and eventually material properties, design and features (seat harmony). Data from previous studies is fine tuned and will be validated in the nominated contexts and markets in follow-up dedicated studies.

Seat Comfort. M1

This literature review reports on high quality research studies focused on measuring occupant comfort in automotive vehicles. The review covers the most important variables in automotive seating design that impact on occupant comfort. These findings will help Futuris and the University develop the target settings that will be measured during the testing phase of the C3-21 project. The review also provides valuable information that may be incorporated into the final comfort procedure that will be developed.

Predicting reduced driver alertness on monotonous highways : a driving simulator study

Impaired driver alertness increases the likelihood of drivers’ making mistakes and reacting too late to unexpected events while driving. This is particularly a concern on monotonous roads, where a driver’s attention can decrease rapidly. While effective countermeasures do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behavior in real-time. The aim of this study is to predict drivers’ level of alertness through surrogate measures collected from in-vehicle sensors. Electroencephalographic activity is used as a reference to evaluate alertness. Based on a sample of 25 drivers, data was collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device. Various classification models were tested from linear regressions to Bayesians and data mining techniques. Results indicated that Neural Networks were the most efficient model in detecting lapses in alertness. Findings also show that reduced alertness can be predicted up to 5 minutes in advance with 90% accuracy, using surrogate measures such as time to line crossing, blink frequency and skin conductance level. Such a method could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring, in real-time, drivers' behavior on highways.

Measuring in-vehicle child comfort to study barriers to appropriate and correct use of restraints

Traffic crashes are the leading cause of death and injury among children aged between 4-14 years1,2 and premature graduation to adult seat belts2,3 and restraint misuse4 are common and known risk factors. Children are believed to prematurely graduate to adult belts and misuse the seat belt in booster seats if uncomfortable2,5,6. Although research has concentrated on educating parents and designing better restraints to reduce errors in use, comfort of the child in the restraint has not been studied. Currently there is no existing method for studying comfort in children in restraint systems, although self-report survey tools and pressure distribution mapping is commonly used to measure comfort among adult in vehicle seats. This poster presents preliminary results from work aimed at developing an appropriate method to measure comfort of children in vehicle restraint systems. The specific aims are to: 1. Examine the potential of using modified adult self-report/survey and pressure distribution mapping in children 2. Develop a video based, objective measure of comfort in children.

A statistical model for combustion resonance from a DI diesel engine with applications

Introduced in this paper is a Bayesian model for isolating the resonant frequency from combustion chamber resonance. The model shown in this paper focused on characterising the initial rise in the resonant frequency to investigate the rise of in-cylinder bulk temperature associated with combustion. By resolving the model parameters, it is possible to determine: the start of pre-mixed combustion, the start of diffusion combustion, the initial resonant frequency, the resonant frequency as a function of crank angle, the in-cylinder bulk temperature as a function of crank angle and the trapped mass as a function of crank angle. The Bayesian method allows for individual cycles to be examined without cycle-averaging|allowing inter-cycle variability studies. Results are shown for a turbo-charged, common-rail compression ignition engine run at 2000 rpm and full load.

A simulator evaluation of effects of assistive technologies on driver cognitive load at railway level crossings

Intelligent Transport Systems (ITS) have the potential to substantially reduce the number of crashes caused by human errors at railway levels crossings. However, such systems could overwhelm drivers, generate different types of driver errors and have negative effects on safety at level crossing. The literature shows an increasing interest for new ITS for increasing driver situational awareness at level crossings, as well as evaluations of such new systems on compliance. To our knowledge, the potential negative effects of such technologies have not been comprehensively evaluated yet. This study aimed at assessing the effect of different ITS interventions, designed to enhance driver behaviour at railway crossings, on driver’s cognitive loads. Fifty eight participants took part in a driving simulator study in which three ITS devices were tested: an in-vehicle visual ITS, an in-vehicle audio ITS, and an on-road valet system. Driver cognitive load was objectively and subjectively assessed for each ITS intervention. Objective data were collected from a heart rate monitor and an eye tracker, while subjective data was collected with the NASA-TLX questionnaire. Overall, results indicated that the three trialled technologies did not result in significant changes in cognitive load while approaching crossings.

Security issues for future intelligent transport systems

Cooperative Intelligent Transportation Systems (C-ITS) allow in-vehicle systems, and ultimately the driver, to enhance their awareness of their surroundings by enabling communication between vehicles and road infrastructure. C-ITS are widely considered as the next major step in driving assistance systems, aiming at increasing safety, comfort and mobility for drivers. However, any communicating systems are subjected to security threats. A key component for providing secure communications at a large scale is a Public Key Infrastructure (PKI). Due to the safety-critical nature of Vehicle-to-Vehicle (V2V) communications, a C-ITS PKI has functional, performance and scalability requirements that differ from traditional non-automotive environments. This paper identifies and defines the key functional and security requirements for C-ITS PKI systems and analyses proposed C-ITS PKI standards against these requirements. In particular, the proposed US and European C-ITS PKI systems are identified as being too complex and not scalable. The paper also highlights various privacy, security and scalability concerns that should be considered for a secure C-ITS PKI solution in the Australian transport landscape.

The Australian naturalistic driving study: From beginnings to launch

The Australian Naturalistic Driving Study (ANDS), a ground-breaking study of Australian driver behaviour and performance, was officially launched on April 21st, 2015 at UNSW. The ANDS project will provide a realistic perspective on the causes of vehicle crashes and near miss crash events, along with the roles speeding, distraction and other factors have on such events. A total of 360 volunteer drivers across NSW and Victoria - 180 in NSW and 180 in Victoria - will be monitored by a Data Acquisition System (DAS) recording continuously for 4 months their driving behaviour using a suite of cameras and sensors. Participants’ driving behaviour (e.g. gaze), the behaviour of their vehicle (e.g. speed, lane position) and the behaviour of other road users with whom they interact in normal and safety-critical situations will be recorded. Planning of the ANDS commenced over two years ago in June 2013 when the Multi-Institutional Agreement for a grant supporting the equipment purchase and assembly phase was signed by parties involved in this large scale $4 million study (5 university accident research centres, 3 government regulators, 2 third party insurers and 2 industry partners). The program’s second development phase commenced a year later in June 2014 after a second grant was awarded. This paper presents an insider's view into that two year process leading up to the launch, and outlines issues that arose in the set-up phase of the study and how these were addressed. This information will be useful to other organisations considering setting up an NDS.