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In this current fast-paced world, releasing a defect free product on time is of utmost importance in the automotive domain. The automobile powertrain is designed with a fine balance of weight and power. Clutch, an intermediate part between engine & transmission in manual transmission vehicle plays crucial role for vehicle smooth drive & functionality. Hydraulic clutch slave cylinder (CSC) which is a part of clutch release system was observed with one failure mode in one of the vehicles during internal road validation. It facilitates to actuate the clutch diaphragm in order to disengage the clutch when clutch pedal is pressed and to re-engage the clutch back when the clutch pedal is released. CSC failure directly disconnects the response of leg to clutch and thus driver may lose vehicle control and can possibly cause a severe vehicle crash.

A new method is demonstrated for rating the “severity” of a hypoid gear set duty cycle (revolutions at torque) using the intercept of T-N curve to support gearset selection and sizing decision across vehicle programs. Historically, it has been customary to compute a cumulative damage (using Miner's Rule) for a rotating component duty cycle given a T-N curve slope and intercept for the component and failure mode of interest. The slope and intercept of a T-N curve is often proprietary to the axle manufacturer and are not published. Therefore, for upfront sizing and selection purposes representative T-N properties are used to assess relative component duty cycle severity via cumulative damage (non-dimensional quantity). A similar duty cycle severity rating can also be achieved by computing the intercept of the T-N curve instead of cumulative damage, which is the focus of this study.

In electric vehicles, there is a continuous shift in the charging and discharging of the battery due to energy generation and regeneration. This adds up to the total number of charging-discharging cycles of the battery. This fluctuation amounts to faster battery degradation and life-cycle reduction. Also, we are exploring solutions to improve the low regeneration efficiency of EVs. For example, overall regeneration efficiency from wheels-to-wheels is only around 64% in Tesla Roadster. Even in current EV powertrains, the regeneration efficiency only reaches up to around 75%, which is much lower compared to the potential efficiency of flywheel-based energy storage (FES) as no energy conversion takes place from one form to another. We implemented FESS in a parallel hybrid setup solely for regenerative braking. Based on the power requirements from the vehicle, the drivetrain smartly switches its power source between the Electric motor and flywheel during the drive cycle.

In order to improve the driving experience of drivers and the efficiency of vehicle development, a method of objective drivability for passenger car powertrain is proposed, which is based on prior knowledge, principal component analysis (PCA) and SMART principle. First, drivability parameters of powertrain for passenger cars are determined according to working principle of powertrain, including engine torque, engine speed, gearbox position, accelerate pedal, brake pedal, steering wheel angle, longitudinal acceleration and lateral acceleration, etc. The drivability quantitative index system is designed based on field test data, prior knowledge and SMART principles. Then, D-S evidence theory and sliding window method are applied to identify objective drivability evaluation conditions of powertrain for passenger cars, including static gearshift conditions, starting conditions, creep conditions, tip-in, tip out, upshift conditions, acceleration, downshift conditions and de-acceleration.

Non-exhaust and exhaust particles from traffic were evaluated to account for nearly equal proportions in traffic-related emissions. Among non-exhaust emissions, tyre wear has been a crucial contributor to Particulate matter (PM), with its mass contribution as high as 30% to non-exhaust emissions from traffic. As exhaust emissions control regulation becomes stricter, which leads to a substantial reduction in exhaust emissions from road traffic, currently relative contributions of non-exhaust particles generated from tyre wear to PM is becoming more important. Accordingly, possible regulatory requirement and effectively control strategy of tyre wear particles needs to be developed. This review paper covers the physical properties, chemical composition, emission rates, and mathematic model development of tyre wear particles.

Gasoline direct injection (GDI) engines usually emit higher levels of particulates in warm-up conditions of a driving cycle. Thus, sources of soot formation in these conditions were investigated by measuring particulate numbers (PN) emitted from a single-cylinder GDI engine and their sizes. The combustion was also visualized using an endoscope connected to a high-speed camera. Engine coolant and oil temperatures were varied between 15 and 90oC to mimic warm-up conditions. In addition, effects of delaying the start of ignition (SOI) on the emissions in these conditions were examined. Coolant and oil temperatures were varied individually to identify which factor has most effect on PN emissions. While coolant temperature strongly influenced PN with cold oil, the oil temperature insignificantly affected PN at low coolant temperature. These findings indicate that PN emissions are heavily dependent on the engine block’s temperature, which is dominated by the coolant.

A gasoline’s chemical composition impacts a vehicle’s sooting tendency and therefore has been the subject of numerous emissions studies. From these studies, several mathematical correlation equations have been developed to predict a gasoline’s sooting tendency in modern spark-ignited internal combustion engine vehicles. This paper reviews the recently developed predictive tool methods and summarizes five years of global market fuel survey data to characterize gasoline sooting tendency trends around the world. Additionally, the paper will evaluate and suggest changes to the predictive methods to improve emissions correlations.

Particulate matter (PM) and NOX are two major pollutants generated by diesel engines. Modern diesel aftertreatment systems include selective catalytic reduction (SCR) technology that helps reduce tailpipe NOX emissions when coupled with diesel exhaust fluid (DEF/urea) injection. However, this process also results in the formation of urea derived byproducts that can influence non-volatile particle number (PN) measurement conducted in accordance with the European Union (EU) Particle Measurement Program (PMP) protocol. In this program, an experimental investigation of the impact of DEF injection on tailpipe PN and its implications for PMP compliant measurements was conducted using a 2015 model year 6.7 L diesel engine equipped with a diesel oxidation catalyst, diesel particulate filter and SCR system. Open access to the engine controller was available to manually override select parameters.

Many factors could affect the detection of a leak on a vehicle fuel evaporative system. This paper investigates the impacts of orifice diameter, tank ullage volume, initial decay pressure, and hot soak temperature. The leak in the fuel evaporation system of a gasoline vehicle was simulated by using the orifices with standard diameters. The pressure decay method was utilized in orifice diameter, ullage volume, and initial decay pressure experiments. This method utilizes an air compressor to establish a certain pressure for the system, after which the orifice is turned open and the pressure change overtime is recorded. Engine off nature vacuum method was utilized in hot soak experiments. After the hot soak in an aging room, the evaporation system was moved to a lower-temperature environment, then the pressure change was recorded. The results show that the larger the diameter of the orifice, the shorter the pressure decay duration.

The authors present a portable NH3 and N2O analyzer utilizing mid-infrared laser absorption spectroscopy for on-board emission measurements. The developed analyzer employs a newly developed absorption spectroscopy named “infrared laser absorption modulation”, hereinafter referred to as IRLAM, for the signal acquisition and concentration determination. Because of IRLAM’s simple and robust signal processing scheme, a highly sensitive, selective and robust measurement system can be realized within a compact size. The following performance metrics of the new analyzer are presented: linearity, detection limit, response time and zero/span drift. Notably, the detection limit (defined as 2σ of the zero signal) of ≤ 0.1 ppm is achieved in both NH3 and N2O measurements. The influence of vibration, and changes in environment conditions such as ambient temperature and atmospheric pressure, are also tested.

Engine and vehicle tailpipe emissions can be measured in laboratories equipped with engine dynamometers and chassis dynamometers, respectively. In addition to laboratory testing, there is an increase in interest to measure on-road vehicle emissions using portable emissions measurement systems in order to determine real-driving emissions. Current methods to quantify engine, vehicle tailpipe, and real-driving emissions include the raw continuous, dilute continuous, and dilute bag measurement methods. Although the dilute bag measurement method is robust, recent improvements to the raw and dilute continuous measurement methods can account for the time delay between the probe tip and analyzer in addition to gas transport dynamics in order to reliably recover the tailpipe concentration signals. These improvements significantly increase the reliability of results using the raw and dilute continuous measurement methods, making them possible alternatives to the bag method.

The general objectives of this research are the identification of relevant factors that influence the movement and rotation behavior of the piston pin and to characterize the oil filling ratio in the piston boss. For this purpose, an experimental measurement campaign with load and speed variation is carried out on an engine test bench. The key challenge is the implementation of the extensive measurement technology on a series V6 engine. For the detection of the radial piston pin movement in stroke and transversal direction four eddy current sensors are used, two per direction. With a combined measuring principle the oil filling ratio can be determinated. Therefore two additional capacitive sensors are placed between the eddy current sensors. Depending on the hydrodynamic friction conditions in the piston pin bearing as well as the thermal and mechanical boundary conditions, the pivoting movement of the connecting rod initiates the rotation of the piston pin.

Air-fuel ratio (AFR) is one of the factors which most influences performances and emissions in internal combustion engine (ICE). Since the chemical content of exhaust gases are directly linked to the composition of fuel and air introduced in the engine, engineers have always been looking for correlations that could evaluate the AFR for each engine operating condition based on exhaust gas emissions. These relations allow to determine the effective AFR at which the engine is running. In the first part of this paper, the main correlations available in literature are reviewed pointing out their hypothesis and assumptions. Then the base Spindt formula and two of its generalizations are applied to the experimental data obtained from a gasoline direct injection supercharged engine. Subsequently the contribution added on the AFR computation by each exhaust compound has been evaluated in order to understand its weights on the final AFR value.

The rising concerns of emissions have put enormous strain on the automotive industry. Industry is, therefore looking for next-generation engines and advanced combustion technologies with ultra-low emissions and high efficiency. To achieve this, more insights into the combustion and pollutant formation processes in IC engines is required. Since conventional measures have not been insightful, in-situ measurement of combustion and pollution formation through optical diagnostics is being explored. Gaining full optical access into the diesel engine combustion chamber is a challenging task. The late-compression flow dynamics is not well understood due to limited access into the engine combustion chamber. These flow structures contribute immensely to fuel-air mixing and combustion. The objective of this study is to understand the role of combustion chamber design on vertical plane air-flow structures.

To improve the thermal efficiency of next-generation engines, the cylinder pressure will be increased further, and thermal load is expected to increase. In addition, to reduce friction loss, the use of low viscosity oils is also being considered. These changes will make the sliding condition of piston rings much more severe, especially for Heavy Duty Diesel (HDD) engines. Therefore, piston rings require surface treatment on their peripheral surface, not only to prevent wear and scuffing, but also to reduce the friction force. Consequently, Diamond-like Carbon (DLC) coatings have been adopted recently as surface treatment for piston rings. However, heat resistance of DLC coatings is known to be low, and suggestions have been made that these coatings are not suitable for use under high temperature environment.

In the ongoing competition of powertrain concepts the Internal Combustion Engine (ICE) will also have to demonstrate its potential for increased efficiency [1]. Variable Compression Ratio (VCR) Systems for Internal Combustion Engines (ICE) can make an important contribution to meeting stringent global fuel economy and CO2 standards. Using such technology a CO2 reduction of between 5% and 9% in the World Harmonized Light-Duty Vehicle Test Cycle (WLTC) are achievable, depending on vehicle class, load profile and power rating [2]. This paper provides a detailed description of the measurement approaches that are used during development of the AVL Dual Mode VCSTM and other VCR systems in fired operation. Results obtained from these measurements are typically used to calibrate or verify simulation models, which themselves are an integral part of the development of these systems [3].

As an important means of engine development and optimization, modelbuilding plays an increasingly important role in reducing carbon dioxide emissions of the internal combustion engines (ICEs). However, due to the non-linearity and high dimension of the engine system, a large amount of data is required to obtain high model accuracy. Therefore, a modelling approach combining the experimental data and prior knowledge was proposed in this study. With this method, an artificial neural network (ANN) model simulating the engine brake specific fuel consumption (BSFC) was established. With mean square error (MSE) and Kullback-Leibler divergence (KLD) serving as the fitness functions, the 86 experimental samples and constructed physical models were used to optimize the ANN weights through genetic algorithms.

With the advancement of engine technologies and combustion strategies, aftertreatment architectures are expected to evolve as they continue to be the primary emissions mitigation hardware. Some of the engine approaches offer unique challenges and benefits that are not well understood beyond criteria pollutant emissions. As such, there continues to be a need to quantify engine emissions characteristics in pursuit of catalyst technology development and the use of advanced simulation tools. The following study discusses results from an extensive engine emissions assessment for current state-of-the-art technology and novel combustion regimes. The engines tested include a Tier 4 final compliant 6.8 L John Deere PSS 6068 diesel engine, a modified 15 L diesel engine, and a dual fuel 13 L natural gas-diesel engine. The dual fuel engine could operate in conventional positive ignition mode (CDF) or low temperature reactivity-controlled compression ignition mode (RCCI).

Considering worldwide future emission and CO2-legislation for the Light Commercial Vehicle segment, a wide range of powertrain variants is expected. Dependent on the application use cases all powertrain combinations, from pure Diesel engine propulsion via various levels of hybridization, to pure battery electric vehicles will be in the market. Under this aspect as well as facing differing legal and market requirements, a modular approach is presented for the LCV and SUV Segment, which can be adapted flexibly to meet the different requirements. A displacement range of 2.0L to 2.3L, representing the current baseline in Europe is taken as basis. To best fulfill the commercial boundaries, tailored technology packages, based on a common global engine platform are defined and compared. These packages include engine related technical features for emission- and fuel consumption improvement, as well as electrification measures, in particular 48V-MHEV variants.

Dual-fuel combustion engines have shown the potential to extend the operating range of Homogeneous Charge Compression Ignition (HCCI) by using several combustion modes, e.g. Reactivity Controlled Compression Ignition (RCCI) at low/medium load, and Partially Premixed Compression (PPC) at high load. In order to optimize the combustion mode operation, the respective sensitivity to the control inputs must be addressed. To this end, in this work the extremum seeking algorithm has been investigated. By definition, this technique allows to detect the control input authority over the system by perturbing its value by a known periodic signal. By analyzing the system response and calculating its gradient, the control input can be adjusted to reach optimal operation. This method has been applied to a dual-fuel engine under fully, highly and partially premixed conditions where the feedback information was provided by in-cylinder pressure and NOx sensors.