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This paper describes a new range of 4 cyl, in-line, single OHC engines produced by Ford in Europe, which is available in three displacements of 1.3, 1.6, and 2.0 1. This engine has been developed for high performance output, high-speed operation, and compliance with various exhaust emission regulations. The significant design features highlighted here are the cylinder block, the cylinder head, the valve arrangement, the intake manifolds, and air cleaners with an air intake pre-heat system, all of which are described here. To establish reliability of this new engine, special test runs were made of 300 engines under customer driving conditions in many countries, covering a total of approximately 10 million km.

One of the ways to reduce city congestion is to balance the traffic flow on the road network and maximally utilize all road capacities. There are examples showing that, if the drivers are not competitive but cooperative, the road network usage efficiency and the traffic conditions can be improved. This motivates the idea of designing a cooperative routing algorithm to benefit most vehicles on the road. This paper presents a semi-cooperative social routing algorithm for large transportation network with predictive traffic density information. The goal is to integrate a cooperative scheme into the individual routing and achieve short traveling time not only for the traveler itself, but also for all vehicles in the road network. The most important concept of this algorithm is that the route is generated with the awareness of the total travel time added to all other vehicles on the road due to the increased congestion.

The rapid development of connected and automated vehicle technologies together with cloud-based mobility services are revolutionizing the transportation industry. As a result, huge amounts of data are being generated, collected, and utilized, hence providing tremendous business opportunities. However, this big data poses serious challenges mainly in terms of data privacy. The risks of privacy leakage are amplified by the information sharing nature of emerging mobility services and the recent advances in data analytics. In this paper, we provide an overview of the connected vehicle landscape and point out potential privacy threats. We demonstrate two of the risks, namely additional individual information inference and user de-anonymization, through concrete attack designs. We also propose corresponding countermeasures to defend against such privacy attacks. We evaluate the feasibility of such attacks and our defense strategies using real world vehicular data.

To meet legal requirements vehicle manufacturers have to use a standard drive-by noise acceleration test conforming to relatively easily specified procedures (gear, approach speed etc). However, due to the transient conditions occurring during the test, predicting maximum drive-by noise levels from the contributions of vehicle systems is difficult. As manufacturers need to identify early in the design of a vehicle those available systems which will ensure legal requirements are met, a technique is required that can predict the contribution of each system. The technique has to be able to accept system target & CAE data as well as test data in order that it can be used in all stages of a vehicle program.

As intelligent automated vehicle technologies evolve, there is a greater need to understand and define the role of the human user, whether completely hands-off (L5) or partly hands-on. At all levels of automation, the human occupant may feel anxious or ill-at-ease. This may reflect as higher stress/workload. The study in this paper further refines how perceived workload may be determined based on occupant physiological measures. Because of great variation in individual personalities, age, driving experiences, gender, etc., a generic model applicable to all could not be developed. Rather, individual workload models that used physiological and vehicle measures were developed.

A computer model solving the 1-D flow in a typical fuel injection system for direct-injection diesel engines is presented. A Bosch distributor - type VE pump connected to four Stanadyne pencil - type nozzles has been used to validate the computer model over a wide range of operating conditions. Validation of the developed computer code has been performed for eight representative test cases. The predicted values which were compared with the experimental ones include the pumping chamber pressure, the line pressure, the needle lift and the injection rate. Results using as input the measured pumping chamber pressure are also presented in order to identify the error in the injection rate signal attributed to the difference between the simulated and the experimental pumping chamber pressure. In addition, the total fuel injection quantity for pump speeds between 500 and 2000 rpm and lever positions between 20% to 100% was calculated and compared with measurements.

The rapid heating of an under-body catalyst after cold start by combustion of rich engine products with added secondary air is described. The results of initial durability studies including spark plug fouling, oil dilution and thermal shock are presented, together with emissions performance and a mileage accumulation study. Also discussed are failure mode assessment and the system tolerance to anticipated open-loop errors and real-world driving scenarios.

This paper discusses how the orientation of fiber in fiber-reinforced plastics affects automotive applications. Orientation can adversely affect moldings in applications where stress is important, especially in engine components such as front timing covers, pump flanges, oil sump bosses, and crankshaft housing. The paper examines these problems in detail and suggests ways to avert serious difficulties relating to fiber orientation.

Air filter elements have been around since the dawn of automotive development. The function of an air induction system and the filter element in particular is to remove particulates such as dust, soot, and relatively minor contaminants from the air flow. This protects the engine, turbocharger, and other components from wear. However, sometimes severe duty cycles may cause large amounts of dust, mud, and water to enter the air induction system (AIS). This can cause filter degradation and even rupture or deformation, leading to highly increased engine and turbocharger wear. One example of this extreme loading is the tar sands region of Alberta, Canada, where trucks can accumulate over 1000 pounds of mud on a vehicle during normal usage over a few weeks’ time. Significant amounts of this mud also get ingested into the AIS. This study attempts to analyze different aspects of filter design to increase robustness to severe usage, particularly mud.

The construction of the Ford ELTEC (Electronic Technology) vehicle has offered a unique opportunity to demonstrate the practical advantages of using modern electronics in a family car. Included in the specification is the integrated control of a lean burn engine and a continuously variable transmission from a single microprocessor. A number of novel features are controlled such as ionisation feedback, intake port, variable geometry induction and an electronic throttle.

The cycle-by-cycle variation of heat transferred per cycle (q) to the combustion chamber surfaces of spark ignition engines has been investigated for quasi-steady and transient conditions produced by throttle movements. The heat transfer calculation is by integration of the instantaneous value over the cycle, using the Woschni correlation for the heat transfer coefficient. By examination of the results obtained, a relatively simple correlation has been identified: This holds both for quasi-steady and transient conditions and is on a per cylinder basis. The analysis has been extended to define a heat flux distribution over the surface of the chamber. This is given by: where F(x/L) is a polynomial function, q″ is the heat transfer per cycle per unit area to head and piston crown surfaces and gives the distribution along the liner

Experimental studies have been carried out on a spark ignition engine with port fuel injection to examine the influence of injector type and to contrast this with the effects of fuel composition. Intake port fuel transport characteristics and engine-out emissions for fully-warm and warm-up engine operating conditions have been examined as indicators of performance. The investigation has encompassed four types of injector and five gasoline blends. Fuel transport has been characterised using the τ and X parameters. The influence of injector type on these is of similar significance as that of changes in gasoline composition between summer and winter grades. The latter will limit the in-service accuracy of open-loop mixture control during transients. Injector type has a small effect on engine-out emissions under fully-warm operating conditions but has a significant influence on emissions during the early stages of warm-up.

Previously reported studies of heat transfer between the intake port surface, gas flows in the port, and fuel deposited in surface films have been extended to examine details of the heat flux variations which occur within the engine cycle. The dynamic response characteristics of the surface-mounted heat flux sensors have been determined, and measured heat flux data corrected accordingly to account for these characteristics. Details of the model and data processing technique used are described. Corrected intra-cycle variations of heat transfer to fuel deposited have been derived for engine operating conditions at 1000 RPM covering a range of manifold pressures, fuel supply rates, port surface temperatures, and fuel injection timings. Both pump-grade gasoline and isooctane fuel have been used. The effects of operating conditions on the magnitude and features of the heat flux variations are described.

The prevention of automotive releases of the unpleasant smelling hydrogen sulfide (H2S) is highly desirable. However, the ability to routinely test catalysts for dynamic H2S releases corresponding to the real world has traditionally proved difficult. The work herein identifies the key steps taken to produce a highly repeatable (overall relative standard deviation of typically less than 10%) procedure capable of replicating H2S releases from wide-open throttle (WOT) events. The testing utilized a chassis dynamometer to test a gasoline vehicle (fitted with one TWC system) over a specific transient drive cycle with H2S emissions detected using a chemical ionization mass spectrometer and an infra-red detection based system. The importance of the warm-up and catalyst preparation parts of the test are discussed, including statistical analysis. A repeatable and short test suited to rapid developmental screening of potential catalyst systems is also presented.

There has been a growing concern about increasing vehicle-mile traveled (VMT) associated with deadhead trips for dynamic rideshare services, particularly with the emergence of Shared Autonomous Vehicle (SAV) services. Studies in the literature on repositioning strategies have been limited to synthetic or small-scale study areas. This study considers a large-scale computational experiment involving a New York City study area with a network of 16,782 nodes and 23,337 links with 662,455 potential travelers from the 2016 Yellow Taxi data. We investigate the potential to reduce VMT and deadhead miles for dynamic rideshare operations combined with vehicle repositioning strategies. Three repositioning strategies are evaluated: (1) Roaming around areas with higher pickup probabilities to maximize the chance of picking up passengers, (2) Staying at curb side after completing trips, and (3) Repositioning to depots to minimize deadhead trips.

Recommender systems guide a user to useful objects in a large space of possible options in a personalized way. In this paper, we study recommender systems for vehicles. Compared to previous research on recommender systems in other domains (e.g., movies or music), there are two major challenges associated with recommending vehicles. First, typical customers purchase fewer cars than movies or pieces of music. Thus, it is difficult to obtain rich information about a customer’s vehicle purchase history. Second, content information obtained about a customer (e.g., demographics, vehicle preferences, etc.) is also difficult to acquire during a relatively short stay in a dealership. To address these two challenges, we propose an interactive vehicle recommender system based a novel machine learning method that integrates decision trees and multi-armed bandits. Decision tree learning effectively selects important questions to ask the customer and encodes the customer's key preferences.

The thermal efficiency of an internal combustion engine at steady state temperatures is typically in the region of 25-35%[1]. In a cold start situation, this reduces to be between 10% and 20% [2]. A significant contributor to the reduced efficiency is poor performance by the engine lubricant. Sub optimal viscosity resulting from cold temperatures leads to poor lubrication and a subsequent increase in friction and fuel consumption. Typically, the engine lubricant takes approximately twenty minutes [3] to reach steady state temperatures. Therefore, if the lubricant can reach its steady state operating temperature sooner, the engine's thermal efficiency will be improved. It is hypothesised that, by decoupling the lubricant from the thermal mass of the surrounding engine architecture, it is possible to reduce the thermal energy loss from the lubricant to the surrounding metal structure in the initial stages of warm-up.

Currently, 80% of European diesel passenger cars are turbocharged and as emission standards become more stringent exhaust gas recirculation (EGR) will be the primary means of suppressing oxides of nitrogen (NOx). The lighter the load the greater will be the combustion tolerance to increased EGR flow rates and hence increased NOx suppression. Automotive diesel engines using wastegated turbochargers cannot recirculate above 50% EGR without some sort of “added” device or system, which is able to displace the inlet fresh air charge. This has been demonstrated by throttling the diesel intake to reduce the fresh air inlet manifold pressure so allowing more EGR flow by virtue of a higher exhaust-side pressure due the effects of the turbocharger. The method reported here investigates a different approach to increasing the EGR rates by replacing a fixed geometry turbocharger (FGT) with a variable geometry turbocharger, (VGT).

Road Load Data is an important source of information for quality improvements. Vehicle and component load information, such as driver behaviour and other characteristics of vehicle use in real world conditions, are the basis for many engineering tasks, including fuel economy and life-time optimization. This new approach in road load data acquisition is based on the increasing existence of data bus networks in modern vehicles, as well as further improvements in data acquisition technologies. The applications of which alllow smart, inobtrusive solutions and, increasingly, the collection of real world customer data. This methodology of data collection leads to a significant alteration of the company-wide data base, relevant for future engineering efforts. The growing share of real world customer data will result in a more optimized and customer-orientated range of solutions, for all areas of vehicle engineering.

With Euro III emissions standards requiring a 50% reduction in current diesel car emissions from January 1st 2000, there is a need to improve fuel consumption and thus reduce exhaust emissions. One of the ways this is being addressed is by the introduction of lower viscosity crankcase oils and by the use of friction modifiers within these oils. The resulting reduced engine friction contributes to improved fuel economy and should also aid engine cold start ability. To investigate the cold start abilities of different crankcase oils, a matrix consisting of six different oil formulations was tested at -20°C, - 25°C and -30°C in a two litre four cylinder diesel engine. The tests were conducted using a dynamometer, with the engine being driven by the dynamometer at nominal cranking speed for 30 seconds and then increased to cold idle speed for a further 30 seconds.