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Abstract Heat release analysis is a widely used cylinder pressure-based method for evaluating combustion in engine development, and it is also being investigated as a means to control engine combustion. Heat release analysis has been shown to be sensitive to errors in the calculated cylinder volume, but despite this one of the most common assumptions is that the cylinder volume is nominal and can be calculated solely by the geometrical relations among the measures of the engine components. During engine operation, the components surrounding the combustion chamber are exposed to thermal forces, pressure forces, and mass forces from the reciprocating components. Due to these forces, the components will deform and the volume of the combustion chamber will deviate from its ideal volume. The volume will also be affected by the production tolerances of the engine.

Abstract Merits such as reduced weight, overall and operational costs of the electric vehicle (EV) while providing level 3 charging capability, are propelling research on integrated charging (IC) technology for EVs. Since the same interior permanent magnet synchronous machine (IPMSM) is used during IC and traction conditions, it is important to understand the behavior of the machine during these conditions and optimally design the machine. Hence, firstly, this paper presents a case study on performance of a laboratory 3-phase IPMSM under IC and traction conditions. Thereafter, understanding the challenges such as low magnet operating point, losses and torque oscillation in 3-phase IPMSM during IC, a 6-phase IPMSM with an unconventional configuration is investigated to yield traction characteristics like that of the 3-phase IPMSM and mitigate challenges during IC. In the process, mathematical model of the 6-phase IPMSM is developed employing the dq-axis theory.

Abstract This work develops a comprehensive thermohydrodynamic (THD) model for high-speed squeeze film dampers (SFDs) in the presence of lubricant inertia effects. Firstly, the generalized expression for Reynolds equation is developed. Additionally, in order to reduce the complexity of the hydrodynamic equations, an average radial viscosity is defined and integrated into the equations. Subsequently, an inertial correction to the pressure is incorporated by using a first-order perturbation technique to represent the effect of lubricant inertia on the hydrodynamic pressure distribution. Furthermore, a thermal model, including the energy equation, the Laplace heat conduction equations in the surrounding solids (i.e. the journal and the bush), and the thermal boundary conditions at the interfaces is constructed. Moreover, the system of partial differential hydrodynamic and thermal equations is simultaneously solved by using an iterative numerical algorithm.

Abstract Significant attention has been focused on Mars due to its relative proximity and possibility of sustaining human life. However, its lack of in-situ sources of energy presents a challenge to generate needed energy on the surface. Comparatively, Titan has a nearly endless source of fuel in its atmosphere and lakes, but both are lacking in regards to their oxidizing capacity. The finding of a possible underground liquid ammonia-water lake on Titan suggests that oxygen might actually be within reach. This effort provides the first theoretical study involving a primary energy generation system on Titan using the atmosphere as a fuel and underground water as the source for the oxygen via electrolysis from wind generated electricity.

Abstract The main objective of active downsizing is to increase the power train efficiency. In order to consistently enhance an approach of active downsizing, it is inevitable to disable and additionally to disengage part of the overall engine displacement volume. The disengagement avoids the friction loss of the piston group as well as its crank- and valve-train section. Therefore, this beneficial approach, the Split-Crankshaft Engine (SCE) is currently under development at the Chair of Internal Combustion Engines in cooperation with the Gear Research Centre (FZG), at the Technical University of Munich. The SCE concept consists of two partial internal combustion engines, which are arranged inline. The Primary Engine (PE) is permanently running while the Secondary Engine (SE) can be switched on and off load-dependently during driving operation.

Abstract Turbulent jet ignition (TJI) is a pre-chamber initiated combustion technology that has been demonstrated to provide low temperature, faster burn rate combustion of lean and intake charge diluted air-fuel mixtures. Dual mode turbulent jet ignition (DM-TJI) is a novel concept wherein a separate air supply is provided for the pre-chamber apart from the conventional auxiliary fuel as supplied for TJI systems. The current study aims to extend the lean flammability limit of a gasoline-fueled engine using DM-TJI. Ignition delay time and combustion behavior of ultra-lean iso-octane/air mixture (Lambda ≅ 3.0) was studied using a TJI-based optically accessible rapid compression machine. High-speed fuel spray recordings in the pre-chamber were obtained using borescope imaging setup. Images of the reacting turbulent jet and subsequent combustion in the main chamber were captured using a visible color camera.

Abstract In this paper, the results of experiments to determine the effects of silicon-containing compounds in biogas on the performance of spark-ignited gas engines for use in CNG vehicles are presented. Initial research was performed on micro-CHP units, which have many features common with automotive engines, to identify engine components sensitive for silica deposition prior to investigating a practical CNG engine. The experiments on the micro-CHP units revealed that the catalyst was the most sensitive part for silica fouling, with strong impact on the reduction of NOx. With the insight gained from these experiments, an 9-week endurance test was performed on a light-duty CNG vehicle.

Abstract Homogeneous lean operation is a well-known strategy for enhancing the thermal efficiency of SI-engines. At higher load points the efficiency is often compromised by the need to suppress knock. Experiments were performed to determine the knock characteristics of SI engines using homogeneous lean operation at λ values of up to 1.8 with various hardware configurations that are commonly used to increase the lean limit. Changing λ altered the eigenfrequencies of the combustion chamber and the highest energy excitation mode. Increasing λ from 1.0 to 1.2 increased the knock tendency and led to an earlier knock onset. However, further increases in λ significantly reduced the knock tendency and retarded the knock onset. The knock signal energy increased for higher λ values and constant knock tendencies. The differences in knock characteristics between the various λ values became more pronounced upon raising the intake temperature from 40 °C to 90 °C.

Abstract CNG is at present retaining a growing interest as a factual alternative to traditional fuels for SI engines, thanks to its high potentials in reducing the engine-out emissions. Increasing thrust into the exploitation of NG in the transport field is in fact produced by the even more stringent emission regulations that are being introduced into the worldwide scenario. Moreover, the transport sector accounts for the 27% of the overall energy consumptions and up to the 13% in terms of global emissions. The present paper aims at deeply investigating into the potentials of a heavy-duty engine running on CNG and equipped with two different injection systems, an advanced single point (SP) one and a prototype multi-point (MP) one. The considered 7.8-liter engine was designed and produced to implement a SP strategy and hence modified to run with a dedicated MP system.

Abstract Driver drowsiness is the cause of many fatal accidents all over the world. Many research works have been conducted on detecting driver drowsiness for more than half a century, but statistical data show that such accidents have not decreased significantly. Most researchers have focused on using certain sensors and extracting their relevant features. However, there has been no research work on developing an algorithm to detect driver drowsiness independently from the input type. In this paper, a hybrid fuzzy-reinforcement learning drowsiness detection algorithm is presented. This algorithm is flexible to work with any number and any kind of data related to driver alertness. It estimates the level of alertness based on an arbitrary number of inputs. The algorithm extracts driving patterns specific to each driver and determines driver’s level of drowsiness using a continuous numerical variable rather than a discrete variable.

Abstract An experimental study was conducted in a direct-injection (DI) spark-ignited engine to determine the extent to which oil reactivity impacts combustion phasing and knock propensity. Three engine oils were examined: a baseline 20W30 oil from conventional base stock, a 5W30 oil from a synthetic base stock, and a jet oil from a hindered ester base stock. The engine was operated at a constant fueling rate of 24.7 mg/injection for two engine speed conditions (1500 and 2000 rpm) using two cam profile conditions (high and low lift), for a total of four operating conditions. Spark timing sweeps were conducted at each of the four operating conditions. Results were analyzed for an engine oil impact on combustion phasing, cycle-to-cycle variability, combustion duration, knock propensity, and knock intensity. No correlation between engine oil type and any of these performance metrics could be identified.

Abstract Since the tire inflation pressure has a significant influence on safety, comfort and environmental behavior of a vehicle, the choice of the optimal inflation pressure is always a conflict of aims. The development of a highly dynamic Tire Pressure Control System (TPCS) can reduce the conflict of minimal rolling resistance and maximal traction. To study the influence of the tire inflation pressure on longitudinal tire characteristics under laboratory conditions, an experimental sensitivity analysis is performed using a multivalent usable Corner Module Test Rig (CMTR) developed by the Automotive Engineering Group at Technische Universität Ilmenau. The test rig is designed to analyze suspension system and tire characteristics on a roller of the recently installed 4 chassis roller dynamometer. Camber angle, toe angle and wheel load can be adjusted continuously. In addition, it is possible to control the temperature of the test environment between −20 °C and +45 °C.

Abstract This study aims to take the first step in bridging the gap between vehicle dynamics systems and autonomous control strategies research. More specifically, a nested method is employed to evaluate the collision avoidance ability of autonomous vehicles in the primary design stage theoretically based on both dynamics and control parameters. An integrated model is derived from a half car mathematical model in the lateral direction, consisting of two degrees of freedom, lateral deviation and yaw angle, with a traction mathematical model in the longitudinal direction, consisting of two degrees of freedom, the longitudinal velocity and rolling velocity of the wheel. The integrated model uses a mathematical power train model to generate the torque on the wheel and connects the two systems via the magic formula tyre model to represent the tyre non-linearity during augmented longitudinal and lateral dynamic attitudes.

Abstract In order to improve robustness of vehicle dynamic performance, a steering mechanism model is proposed with alignment parameters of front wheel based on preference function method. In the steering mechanism model controllable variables include the trapezoid connection length, the base angle of steering trapezoid, the kingpin inclination angle, caster, camber and uncontrollable variables include load and initial braking velocity. Optimization objective is some vehicle dynamic performance. In the preference function method the individual performance preference and preference aggregation in designing variable space and performance variable space are analyzed. The individual performance preference includes the controllable variable preference, noise factor preference and optimization objective preference. The aggregation function is developed by aggregating all the individual performance preferences.

Abstract Under contract to the EPA, Eastern Research Group analyzed light-duty vehicle OBD monitor readiness and diagnostic trouble codes (DTCs) using inspection and maintenance (I/M) data from four states. Results from roadside pullover emissions and OBD tests were also compared with same-vehicle I/M OBD results from one of the states. Analysis focused on the evaporative emissions control (evap) system, the catalytic converter (catalyst), the exhaust gas recirculation (EGR) system and the oxygen sensor and oxygen sensor heater (O2 system). Evap and catalyst monitors had similar overall readiness rates (90% to 95%), while the EGR and O2 systems had higher readiness rates (95% to 98%). Approximately 0.7% to 2.5% of inspection cycles with a “ready” evap monitor had at least one stored evap DTC, but DTC rates were under 1% for the catalyst and EGR systems, and under 1.1% for the O2 system, in the states with enforced OBD programs.

Abstract Increasingly stringent emissions standards and the related efforts to increase vehicle fuel economy have forced the development and implementation of many new technologies. In the light-duty, passenger vehicle segment, one key strategy has been downsized, down-sped, boosted engines. Gasoline direct injection, coupled with turbocharging, have allowed for a drastic reduction in engine size while maintaining or improving engine performance. However, obtaining more power from a smaller engine has produced some consequences. One major consequence is the uncontrolled combustion known as Low Speed Pre-Ignition (LSPI). LSPI and the high energy knocking event which frequently follows have been known to result in fractured pistons and catastrophic engine failure. The propensity at which LSPI occurs has been linked to engine oil formulation.

Abstract Bio-fuels of the 2nd generation constitute a key approach to tackle both Greenhouse Gas (GHG) and air quality challenges associated with combustion emissions of the transport sector. Since these fuels are obtained of residual materials of the agricultural industry, well-to-tank CO2 emissions can be significantly lowered by a closed-cycle of formation and absorption of CO2. Furthermore, studies of bio-fuels have shown reduced formation of particulate matter on account of the fuels’ high oxygen content therefore addressing air quality issues. However, due to the high oxygen content and other physical parameters these fuels are expected to exhibit different ignition behaviour. Moreover, the question is whether there is a positive superimposition of the fuels ignition behaviour with the benefits of an alternative ignition system, such as a corona ignition.

Abstract Wet clutch packs are the key component for gear shifting in the step-ratio automatic transmission system. The clutch plates are coupled or de-coupled to alter gear ratios based on the driver’s actions and vehicle operating conditions. The frictional interfaces between clutch plates are lubricated with automatic transmission fluid (ATF) for both thermal and friction management. In a 10-speed transmission, there may be as many as 6 clutch packs. Under typical driving conditions, 2 to 3 clutch packs are open, shearing ATF and contributing to energy loss. There is an opportunity to improve fuel economy by reducing the associated viscous drag. An important factor that directly affects clutch drag is the clearance between rotating plates. The axial position of clutch plates changes continuously during operation. It is known in practice that not only the total clearance, but also its distribution between the plates affects the viscous drag.

Abstract In this paper, an efficient lane detection using deep feature extraction method is proposed to achieve real-time lane detection in diverse road environment. The method contains three main stages: 1) pre-processing, 2) deep lane feature extraction and 3) lane fitting. In pre-processing stage, the inverse perspective mapping (IPM) is used to obtain a bird's eye view of the road image, and then an edge image is generated using the canny operator. In deep lane feature extraction stage, an advanced lane extraction method is proposed. Firstly, line segment detector (LSD) is applied to achieve the fast line segment detection in the IPM image. After that, a proposed adaptive lane clustering algorithm is employed to gather the adjacent line segments generated by the LSD method. Finally, a proposed local gray value maximum cascaded spatial correlation filter (GMSF) algorithm is used to extract the target lane lines among the multiple lines.

Abstract Obstacle avoidance is an important function in self-driving vehicle control. When the vehicle move from any arbitrary start positions to any target positions in environment, a proper path must avoid both static obstacles and moving obstacles of arbitrary shape. There are many possible scenarios, manually tackling all possible cases will likely yield a too simplistic policy. In this paper reinforcement learning is applied to the problem to form effective strategies. There are two major challenges that make self-driving vehicle different from other robotic tasks. Firstly, in order to control the vehicle precisely, the action space must be continuous which can’t be dealt with by traditional Q-learning. Secondly, self-driving vehicle must satisfy various constraints including vehicle dynamics constraints and traffic rules constraints. Three contributions are made in this paper.