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Single-cylinder spark ignition engine experiments conducted at constant speed, fixed airflow, and using isooctane as the fuel, demonstrated the effects of fuel-air mixture preparation on lean operation. Mixture preparation was changed by varying the time of fuel injection in the induction manifold, near the intake valve port. For comparison, a prevaporized fuel-air mixture was also investigated. Emphasis was placed on determining the effects of mixture preparation on combustion characteristics. Based on the results from this study, the often favored prevaporized mixture of fuel and air may not be the best diet for lean engine operation.

In general for Vehicle-to-Vehicle (V2V) communication, message authentication is performed on every received wireless message by conducting verification for a valid signature, and only messages that have been successfully verified are processed further. In V2V safety communication, there are a large number of vehicles and each vehicle transmits safety messages frequently; therefore the number of received messages per second would be large. Thus authentication of each and every received message, for example based on the IEEE 1609.2 standard, is computationally very expensive and can only be carried out with expensive dedicated cryptographic hardware. An interesting observation is that most of these routine safety messages do not result in driver warnings or control actions since we expect that the safety system would be designed to provide warnings or control actions only when the threat of collision is high.

TFC/IW, total fuel consumption divided by inertia weight is reported with other engineering variables for recent EPA data for industry passenger cars and truck. TFC/IW is used in comparisons between gasoline and diesel engines, 49 States and California, passenger cars and trucks. The California fuel economy penalty due to more stringent emissions standards is discussed. The relationship between TFC/IW and ton miles per gallon is shown. Special attention is focused on 4 cylinder gasoline powered vehicles in 49 States passenger car fleet. The use of TFC/IW to answer the question, ‘What Changed?’ when comparing the fuel economies of two fleets is described.

The SHIFT-MATE is a dashboard mounted computer based device that cues a truck driver to shift more efficiently. Through electronic circuitry, key vehicle parameters are monitored, computed, then via graphic display, instructs the driver when to shift for improved fuel economy. The theory of operation is described in the text.

A large number of testing procedures have been developed to ensure vehicle safety in common and extreme driving situations. However, these conventional testing procedures are insufficient for testing autonomous vehicles. They have to handle unexpected scenarios with the same or less risk a human driver would take. Currently, safety related systems are not adequately tested, e.g. in collision avoidance scenarios with pedestrians. Examples are the change of pedestrian behaviour caused by interaction, environmental influences and personal aspects, which cannot be tested in real environments. It is proposed to use augmented reality techniques. This method can be seen as a new (Augmented) Pedestrian in the Loop testing procedure.

A survey of the in-service fuel consumption of passenger vehicles and derivatives in the Australian fleet was carried out in 1984-85. Seven hundred and four owners across Australia took part in the survey. Vehicle owners reported by questionnaire the amount of fuel used during four tank fills of normal operation, the distance travelled, and other details of the operating circumstances. The survey shows a clear downward trend in the fuel consumption of the Australian passenger fleet. The data also provides comparisons of actual fuel consumption obtained on the road, with laboratory derived values for fuel consumption. Vehicles in a sub-set of 40 were fitted with fuel flow meters during the survey and tested to Australian Standard 2077 for fuel consumption. The questionnaire method is shown to be a valid and accurate technique for determining in-service fuel consumption.

The current research was aimed at determining the most effective way to use alternative renewable feedstock to power a diesel engine. Mimusops elengi, a new and novel biofuel was recognized for this current study, which is widely available in the south of India. The investigation was conducted on B20 volume basis (20% Mimusops elengi methyl ester blended with 80% diesel). Furthermore, it was recognized that when the performance characteristics were traded off, the emission magnitude has slightly higher. To address the diesel engine pollution, an oxygenated nano additive like titanium oxide was dissipated only with the fuel blend at distinct mass fractions of 25 parts per million (ppm) with differing injection pressures of 180 bar, 200 bar, 220 bar, and 240 bar. The tests were created using a statistical programme known as design of experiments, which is purely based on Taguchi and response surface methodology.

A multi vector design tool to accurately predict instrument panel obscuration was developed to insure that critical legal displays in vehicles are not obscured. The concept provides for a computer generated light source shaped to replicate the human eyes. The light source is then projected onto a 3D math based arrangement and the resultant shadows are visible on the instrument panel surface and its displays. Design studios require criteria for the placement of the instrument cluster gages and displays, various controls, switches, and steering column stalks before an interior theme can be completed. Therefore, instrument panel obscuration and visibility must be determined early in the design process. The obscured areas are a function of the instrument panel surface, steering wheel rim, hub, spokes, and the location of the driver's eyes. This light source method allows engineers and designers the ability to quickly determine obscured areas.

The goal of this project was to investigate how to make driver distraction state classification more efficient by applying selected machine learning techniques to existing datasets. The data set used in this project included both overt driver behavior measures (e.g., lane keeping and headway measures) and indices of internal cognitive processes (e.g., driver situation awareness responses) collected under four distraction conditions, including no-distraction, visual-manual distraction only, cognitive distraction only, and dual distraction conditions. The baseline classification method that we employed was a support vector machine (SVM) to first identify driver states of visual-manual distraction and then to identify any cognitive-related distraction among the visual-manual distraction cases and other non-visual manual distraction cases.

Plug-in Hybrid Electric Vehicles (PHEVs) use electric energy from the grid rather than fuel energy for most short trips, therefore drastically reducing fuel consumption. Different configurations can be used for PHEVs. In this study, the parallel pre-transmission, series, and power-split configurations were compared by using global optimization. The latter allows a fair comparison among different powertrains. Each vehicle was operated optimally to ensure that the results would not be biased by non-optimally tuned or designed controllers. All vehicles were sized to have a similar all-electric range (AER), performance, and towing capacity. Several driving cycles and distances were used. The advantages of each powertrain are discussed.

Driver state monitoring is a crucial technology for enhancing road safety and preventing human error-caused accidents in the era of autonomous vehicles. This paper presents CogniSafe, a comprehensive driver monitoring system that uses deep learning and computer vision methods to detect various types of driver distractions and fatigue. CogniSafe consists of four modules: Driver anomaly detection and classification: A novel two-phase network that proposes and recognizes driver anomalies, such as texting, drinking, and adjusting radios, using multimodal and multiview input. Gaze estimation: A video-based neural network that jointly learns head pose and gaze dynamics, achieving robust and efficient gaze estimation across different head poses. Eye state analysis: A multi-tasking CNN that encodes features from both eye and mouth regions, predicting the percentage of eye closure (PERCLOS) and the frequency of mouth opening (FOM).

Due to the rising costs of fuel and increasingly stringent regulations, auto makers are in need of technology to enable more fuel-efficient powertrain technologies to be introduced to the marketplace. Such powertrains must not sacrifice performance, safety or driver comfort. Today's engine and powertrain manufacturers must, therefore, do more with less by achieving acceptable vehicle performance while reducing fuel consumption. One effective method to achieve this is the extreme downsizing of current direct injection spark ignited (DISI) engines through the use of high levels of boosting and cooled exhaust gas recirculation (EGR). Key challenges to highly downsized gasoline engines are retarded combustion to prevent engine knocking and the necessity to operate at air/fuel ratios that are significantly richer than the stoichiometric ratio.

Powertrain electrification is becoming increasingly common in the transportation sector to address the challenges of global warming and deteriorating air quality. This paper introduces a novel “Build Your Hybrid” approach to experience and test various hybrid powertrain concepts. This approach is applied to the light commercial vehicles (LCV) segment due to the attractive combination of a Diesel engine and a partly electrified powertrain. For this purpose, a demonstrator vehicle has been set up with a flexible P02 hybrid topology and a prototype Hybrid Control Unit (HCU). Based on user input, the HCU software modifies the control functions and simulation models to emulate different sub-topologies and levels of hybridization in the demonstrator vehicle. Three powertrain concepts are considered for LCVs: HV P2, 48V P2 and 48V P0 hybrid. Dedicated hybrid control strategies are developed to take full advantage of the synergies of the electrical system and reduce CO2 and NOx emissions.

Consideration of the approaching ‘energy crisis’ reveals two requirements for future light duty automotive engines. 1) maximum economy and 2) the ability (perhaps with detail design re-optimisation) to accept a range of fuels of petroleum or other extract, of differing ignition characteristics. One combustion system which meets these requirements is the MAN ‘FM’, the potential of which has already been demonstrated in truck-size engines but on which little information has been published in light-duty engine bore sizes. The paper describes both design and experimental work carried out to evaluate the application of the FM combustion system to a light duty passenger car engine. Consideration is given to the critical design parameters associated with the application of the FM system to a multi-cylinder gasoline based engine and how the criteria can be met. Details of the design and construction of a single cylinder derivative of the multi-cylinder engine are given.

A cooperation of several research partners supported by the German Federal Ministry of Research and Education proposes a new active matrix LED light source. A multi pixel flip chip LED array is directly mounted to an active driver IC. A total of 1024 pixel can be individually addressed through a serial data bus. Several of these units are integrated in a prototype headlamp to enable advanced light distribution patterns in an evaluation vehicle.

Dynamic skip fire (DSF) has shown significant fuel economy improvement potential via reduction of pumping losses that generally affect throttled spark-ignition (SI) engines. In DSF operation, individual cylinders are fired on-demand near peak efficiency to satisfy driver torque demand. For vehicles with a downsized-boosted 4-cylinder engine, DSF can reduce fuel consumption by 8% in the WLTC (Class 3) drive cycle. The relatively low cost of cylinder deactivation hardware further improves the production value of DSF. Lean burn strategies in gasoline engines have also demonstrated significant fuel efficiency gains resulting from reduced pumping losses and improved thermodynamic characteristics, such as higher specific heat ratio and lower heat losses. Fuel-air mixture stratification is generally required to achieve stable combustion at low loads.

This study proposes a novel biofuel for spark ignition (SI) engine, α-pinene (C10H16), which is non-oxygenated and thus has a gravimetric energy density comparable to that of hydrocarbon fuels. The ignition characteristics of α-pinene were evaluated in an ignition quality tester (IQT) under standard temperature and pressure conditions. The measured ignition delay time (IDT) of α-pinene is 10.5 ms, which is lower than that of iso-octane, 17.9 ms. The estimated research octane number (RON) for pinene from IQT is 85. A temperature sweep in IQT showed that that α-pinene is less reactive at low temperatures, but more reactive at high temperatures when compared to isooctane. These results suggest that α-pinene has high octane sensitivity (OS) and is suitable for operation in turbocharged SI engines. With these considerations, α-pinene was operated in a single cylinder SI engine.

The Swedish Biomimetics 3000's μMist® platform technology has been used to develop a radically new injection system. This prototype system, developed and characterized with support from Lotus, as part of Swedish Biomimetics 3000®'s V₂IO innovation accelerating model, delivers improved combustion efficiency through achieving exceptionally small droplets, at fuel rail pressures far less than conventional GDI systems and as low as PFI systems. The system gives the opportunity to prepare and deliver all of the fuel load for the engine while the intake valves are open and after the exhaust valves have closed, thereby offering the potential to use advanced charge scavenging techniques in PFI engines which have hitherto been restricted to direct-injection engines, and at a lower system cost than a GDI injection system.

This paper deals with the Coupled thermo mechanical analysis of a cylinder head, cylinder block and crank case with the liner of an uprated engine. The existing engine develops 780 hp output with mechanical driven supercharger and the engine is uprated to 1000 hp by replacing the supercharger with a turbocharger and new Fuel injection equipment. For uprating any engine, the piston and cylinder head are the most vulnerable members due to increased mechanical and thermal loadings. Mechanical loading is due to the gas pressure in the gas chamber and its magnitude can be judged in terms of peak pressure. Thermal loading is due to temperature and the heat transfer conditions in the piston surface, cylinder liner and the cylinder head. The relative importance of the various loads applied on the head and cylinder block in operation are assessed and a method of predicting their influence on the structural integrity of the components described.

mDSF is a novel cylinder deactivation technology developed at Tula Technology, which combines the torque control of Dynamic Skip Fire (DSF) with Miller cycle engines to optimize fuel efficiency at minimal cost. mDSF employs a valvetrain with variable valve lift plus deactivation and novel control algorithms founded on Tula’s proven DSF technology. This allows cylinders to dynamically alternate among 3 potential states: high-charge fire, low-charge fire, and skip (deactivation). The low-charge fire state is achieved through an aggressive Miller cycle with Early Intake Valve Closing (EIVC). The three operating states in mDSF can be used to simultaneously optimize engine efficiency and driveline vibrations. Acceleration performance is retained using the all-cylinder, high-charge firing mode.