Search Results

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state).

Vehicle-to-everything (V2X) communication, primarily designed for communication between vehicles and other entities for safety applications, is now being studied for its potential to improve vehicle energy efficiency. In previous work, a 20% reduction in energy consumption was demonstrated on a 2017 Prius Prime using V2X-enabled algorithms. A subsequent phase of the work is targeting an ambitious 30% reduction in energy consumption compared to a baseline. In this paper, we present the Eco-routing algorithm, which is key to achieving these savings. The algorithm identifies the most energy-efficient route between an Origin-Destination (O-D) pair by leveraging information accessible through commercially available Application Programming Interfaces (APIs). This algorithm is evaluated both virtually and experimentally through simulations and dynamometer tests, respectively, and is shown to reduce vehicle energy consumption by 10-15% compared to the baseline over real-world routes.

Hydrogen Internal Combustion Engines (H2 ICE) are gaining recognition as a nearly emission-free alternative to traditional ICE engines. However, H2 ICE systems face challenges related to thermal management, N2O emissions, and reduced SCR efficiency in high humidity conditions (15% H2O). This study assesses how hydrogen in the exhaust affects after-treatment system components for H2 ICE engines, such as Selective Catalytic Reduction (SCR), Hydrogen Oxidation Catalyst (HOC), and Ammonia Slip Catalyst (ASC). Steady-state experiments with inlet H2 inlet concentrations of 0.25% to 1% and gas stream moisture levels of up to 15% H2O were conducted to characterize the catalyst response to H2 ICE exhaust. The data was used to calibrate and validate system component models, forming the basis for a system simulation.

According to the Annual Energy Outlook 2022 (AEO2022) report, almost 30% of the transport sector will still use internal combustion engines (ICE) until 2050. The transportation sector has been actively seeking different methods to reduce the CO2 emissions footprint of fossil fuels. The use of lower carbon-intensity fuels such as Renewable Diesel (RD) can enable a pathway to decarbonize the transport industry. This suggests the need for experimental or advanced numerical studies of RD to gain an understanding of its combustion and emissions performance. This work presents a numerical modeling approach to study the combustion and emissions of RD. The numerical model utilized the development of a reduced chemical kinetic mechanism for RD’s fuel chemistry. The final reduced mechanism for RD consists of 139 species and 721 reactions, which significantly shortened the computational time from using the detailed mechanism.

This program involved the detailed evaluation of a novel laser-based in-exhaust ammonia sensor using a diesel fuel-based burner platform integrated with an ammonia injection system. Test matrix included both steady-state modes and transient operation of the burner platform. Steady-state performance evaluation included tests that examined impact of exhaust gas temperature, gas velocity and ammonia levels on sensor response. Furthermore, cross sensitivity of the sensor was examined at different levels of NOX and water vapor. Transient tests included simulation of the FTP test cycles at different ammonia and NOX levels. A Fourier transform infrared (FTIR) spectrometer as well as NIST traceable ammonia gas bottles (introduced into the exhaust stream via a calibrated flow controller) served as references for ammonia measurement.

Stringent emissions regulations and the need for lower tailpipe emissions are pushing the development of low-carbon alternative fuels. H2 is a zero-carbon fuel that has the potential to lower CO2 emissions from internal combustion engines (ICEs) significantly. Moreover, this fuel can be readily implemented in ICEs with minor modifications. Batteries can be argued to be a good zero tailpipe emission solution for the light-duty sector; however, medium and heavy-duty sectors are also in need of rapid decarbonization. Current strategies for H2 ICEs include modification of the existing spark ignition (SI) engines to run on port fuel injection (PFI) systems with minimal changes from the current compressed natural gas (CNG) engines. This H2 ICE strategy is limited by knock and pre-ignition. One solution is to run very lean (lambda >2), but this results in excessive boosting requirements and may result in high NOx under transient conditions.

This project’s objective was to generate experimental data to evaluate the impact of metals doped B20 on diesel particle filter (DPF) ash loading and performance compared to that of conventional petrodiesel. The effect of metals doped B20 vs. conventional diesel on a DPF was quantified in a laboratory controlled accelerated ash loading study. The ash loading was conducted on two DPFs – one using ULSD fuel and the other on B20 containing metals dopants equivalent to 4 ppm B100 total metals. Engine oil consumption and B20 metals levels were accelerated by a factor of 5, with DPFs loaded to 30 g/L of ash. Details of the ash loading experiment and on-engine DPF performance evaluations are presented in the companion paper (Part I). The DPFs were cleaned, and ash samples were taken from the cleaned material. X-ray Fluorescence (XRF), X-Ray Photoelectron Spectroscopy (XPS) and X-Ray Diffraction (XRD) were conducted on the ash samples.

The project objective was to generate experimental data to evaluate the impact of metals doped B20 on DPF ash loading and performance compared to that of conventional petrodiesel. Accelerated ash loading was conducted on two DPFs – one exposed to regular diesel fuel and the other to B20 containing metal dopants equivalent to 4 ppm B100 total metals (currently total metals are limited to 10 ppm in ASTM D6751, the standard for B100). Periodic performance evaluations were conducted on the DPFs at 10 g/L ash loading intervals. After the evaluations at 30 g/L, the DPF was cleaned with a commercial DPF cleaning machine and another round of DPF evaluations were conducted. A comparison of the effect of ash loading with the two fuels and DPF cleaning is presented. The metals doped B20 fuel resulted in ash that was similar to that deposited when exposed to ULSD (lube oil ash) and exhibited similar ash cleaning removal efficiency.

Vehicle to Everything (V2X) communication has enabled on-board access to information from other vehicles and infrastructure. This information, traditionally used for safety applications, is increasingly being used for improving vehicle fuel economy [1-5]. This work aims to demonstrate energy consumption reductions in heavy/medium duty vehicles using an eco-driving algorithm. The algorithm is enabled by V2X communication and uses data contained in Basic Safety Messages (BSMs) and Signal Phase and Timing (SPaT) to generate an energy-efficient velocity trajectory for the vehicle to follow. An urban corridor was modeled in a microscopic traffic simulation package and was calibrated to match real-world traffic conditions. A nominal reduction of 7% in energy consumption and 6% in trip time was observed in simulations of eco-driving trucks.

As governmental agencies focus on low levels of the oxides of nitrogen (NOx) emissions compliance, new off-road applications are being reviewed for both regulated and unregulated emissions to understand the technological challenges and requirements for improved emissions performance. The California Air Resources Board (CARB) has declared its intention to pursue more stringent NOX standards for the off-road market. As part of this effort, CARB initiated a program to provide a detailed characterization of emissions meeting the current Tier 4 off-road standards [1]. This work focused on understanding the off-road market, establishing a current technology emissions baseline, and performing initial modeling on potential low NOx solutions. This paper discusses a part of this effort, focuses on the emissions characterization from two non-road engine platforms, and compares the emissions species from different approaches designed to meet Tier 4 emissions regulations.

Machine learning algorithms are effective tools to reduce the number of engine dynamometer tests during internal combustion engine development and/or optimization. This paper provides a case study of using such a statistical algorithm to characterize the heat transfer from the combustion chamber to the environment during combustion and during the entire engine cycle. The data for building the machine learning model came from a single cylinder compression ignition engine (13.3 compression ratio) that was converted to natural-gas port fuel injection spark-ignition operation. Engine dynamometer tests investigated several spark timings, equivalence ratios, and engine speeds, which were also used as model inputs. While building the model it was found that adding the intake pressure as another model input improved model efficiency.

A push for more stringent emissions regulations has resulted in larger, increasingly complex aftertreatment solutions. In particular, oxides of nitrogen (NOX) and particulate matter (PM) have been controlled using two separate systems, selective catalytic reduction (SCR) and the catalyze diesel particulate filter (CDPF), or the functionality has been combined into a single device producing the SCR on filter (SCRoF). The SCRoF forgoes beneficial NO2 production present in the CDPF to avoid NH3 oxidation which occurs when using platinum group metals (PGM) for oxidation. In this study, mixed-metal oxides are shown to oxidize NO to NO2 without appreciable NH3 oxidation. This selectivity leads to enhanced performance when combined with a typical Cu-zeolite catalyst.

The size and distribution of a vehicle’s tailpipe particulate emissions can have a strong impact on human health, especially if the particles are small enough to enter the human respiratory system. Gasoline direct injection (GDI) has been adopted widely to meet stringent fuel economy and CO2 regulations across the globe for recent engine architectures. However, the introduction of GDI has led to challenges concerning the particulate matter (PM) and particle number (PN) emissions from such engines. This study aimed to compare the particulate emissions of three SI combustion strategies: conventional SI, conventional stoichiometric low-pressure exhaust gas recirculation (LP-EGR), and Dedicated-EGR (D-EGR) at four specific test conditions. It was shown that the engine-out PM/PN for both the EGR strategies was lower than the conventional SI combustion under normal operating conditions. The test conditions were chosen to represent the WLTC test conditions.

With the increasing level of electrification of on-road, off-road and stationary applications, use of larger lithium-ion battery packs has become essential. These packs require large capital investments on the order of millions of dollars and pose a significant risk of self-annihilation without rigorous safety evaluation and management. Testing these larger battery packs to validate design changes can be cost prohibitive. A reliable numerical simulation tool to predict battery thermal runaway under various abuse scenarios is essential to engineer safety into the battery pack design stage. A comprehensive testing & simulation workflow has been established to calibrate and validate the numerical modeling approach with the test data for each of the individual sub model - electrochemical, internal short circuit and thermal abuse model. A four-equation thermal abuse model was built and validated for lithium-ion 21700 form factor cylindrical cells using NCA cathodes.

Current industry trends in both powertrain electrification and vehicle drag reduction point towards reduced peak and average power demands from the internal combustion engine in future long-haul class 8 vehicles. Downsizing the engine displacement to match these new performance requirements can yield a benefit in drive cycle efficiency through reduced friction and improved cruise load efficiency. Downsizing by reducing cylinder count avoids the heat loss and friction penalties from reduced per-cylinder displacement and could allow a manufacturer to continue to leverage the highly optimized combustion system from existing heavy-duty engines in the new downsized offering. The concept of this study is to leverage powertrain electrification and the improvement trends in vehicle aerodynamics and rolling resistance to develop a fuel economy focused, downsized heavy duty diesel powertrain for future long-haul vehicles utilizing a reduced cylinder count.

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.

Euro VI regulations in Europe and its adaptors recently extended the regulation to include Particle Number (PN) for in-use conformity testing. However, the in-use PN Portable Emissions Measurement System (PEMS) is still evolving and has higher measurement uncertainty when compared against laboratory-grade PN systems. The PN systems for laboratory require a condensation particle counter (CPC). Thus, in this study, a CPC-based Horiba PN-PEMS was selected for performance evaluation against the laboratory-grade PN systems. This study was divided into four phases. The first two phases’ measurements were conducted from the Constant Volume Sampler (CVS) tunnel where the brake-specific particle number (BSPN) levels of 1010-12 and 1013 (#/bhp-h) were measured from the engines equipped with diesel particulate filter (DPF) and without DPF, respectively. In comparison against PN systems, PN-PEMS, on average, reported 14% lower BSPN from 82 various tests for the BSPN levels of 1010-11.

The confluence of increasing fuel economy requirements and increased use of ethanol as a gasoline blend component has led to various studies into the efficiency and performance benefits of higher octane numbers and high ethanol content fuels in modern engines. As part of a comprehensive study of the autoignition of different fuels in both the CFR octane rating engine and a modern, direct injection, turbocharged spark-ignited engine, a series of fuel blends were prepared with varying composition, octane numbers and ethanol blend levels. The paper reports on the third part of this study where cylinder pressures were recorded for fuels under knocking conditions in both a single-cylinder research engine (SCE), utilizing a GM LHU head and piston, as well as the CFR engines used for octane ratings.

It is widely acknowledged that the CFR octane rating engines are not representative of modern engines and that there is a gap in the quantification of knock severity between the two engine types. As part of a comprehensive study of the autoignition of different fuels in both the CFR octane rating engines and a modern, direct injection, turbocharged spark-ignited engine, a series of fuel blends were tested with varying composition, octane numbers and ethanol blend levels. The paper reports on the fourth part of this study where cylinder pressures were recorded under standard knock conditions in CFR engines under RON and MON conditions using the ASTM prescribed instrumentation. By the appropriate signal conditioning of the D1 detonation pickups on the CFR engines, a quantification of the knock severity was possible that had the same frequency response as a cylinder pressure transducer.

As agencies and governing bodies evaluate the feasibility of reduced emission standards, additional focus has been placed on technology durability. This is seen in proposed updates, which would require Original Equipment Manufacturers (OEMs) to certify engine families utilizing a full useful life (FUL) aftertreatment system. These kinds of proposed rulings would place a heavy burden on the manufacturer to generate FUL components utilizing traditional engine aging methods. Complications in this process will also increase the product development effort and will likely limit the amount of aftertreatment durability testing. There is also uncertainty regarding the aging approach and the representative impact compared to field aged units. Existing methodologies have evolved to account for several deterioration mechanisms that, when controlled, can be utilized to create a flexible aging protocol. As a result, these methodologies provide the necessary foundation for continued development.