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Abstract Identity-Anonymized CAN (IA-CAN) protocol is a secure CAN protocol, which provides the sender authentication by inserting a secret sequence of anonymous IDs (A-IDs) shared among the communication nodes. To prevent malicious attacks from the IA-CAN protocol, a secure and robust system error recovery mechanism is required. This article presents a central management method of IA-CAN, named the IA-CAN with a global A-ID, where a gateway plays a central role in the session initiation and system error recovery. Each ECU self-diagnoses the system errors, and (if an error happens) it automatically resynchronizes its A-ID generation by acquiring the recovery information from the gateway. We prototype both a hardware version of an IA-CAN controller and a system for the IA-CAN with a global A-ID using the controller to verify our concept.

Abstract Present-day vehicles come with a variety of new features like the pre-crash warning, the vehicle-to-vehicle communication, semi-autonomous driving systems, telematics, drive by wire. They demand very high bandwidth from in-vehicle networks. Various ECUs present inside the automotive transmits useful information via automotive multiplexing. Transmission of data in real-time achieves optimum functionality. The high bandwidth and high-speed requirement can be achieved either by using multiple buses or by implementing higher bandwidth. But, by doing so, the cost of the network as well as the complexity of the wiring increases. Another option is to implement higher layer protocol which can reduce the amount of data transferred by using data reduction (DR) techniques, thus reducing the bandwidth usage. The implementation cost is minimal as the changes are required in the software only and not in hardware.

Abstract Deep learning (DL)-based approaches enable unprecedented control paradigms for propulsion systems, utilizing recent advances in high-performance computing infrastructure connected to modern vehicles. These approaches can be employed to optimize diesel aftertreatment control systems targeting the reduction of emissions. The optimization of the Trapped Soot Load (TSL) reduction in the Diesel Particulate Filter (DPF) is such an example. As part of the diesel aftertreatment system, the DPF stores the soot particles resulting from the combustion process in the engine. Periodically, the stored soot is oxidized during a DPF regeneration event. The efficiency of such a regeneration influences the fuel economy, and potentially the service interval of the vehicle. The quality of a regeneration depends on the operating conditions of the DPF, the engine, and the ability to complete the regeneration event.

Abstract Automotive software is increasingly complex and critical to safe vehicle operation, and related embedded systems must remain up to date to ensure long-term system performance. Update mechanisms and data modification tools introduce opportunities for malicious actors to compromise these cyber-physical systems, and for trusted actors to mistakenly install incompatible software versions. A distributed and stratified “black box” audit trail for automotive software and data provenance is proposed to assure users, service providers, and original equipment manufacturers (OEMs) of vehicular software integrity and reliability. The proposed black box architecture is both layered and diffuse, employing distributed hash tables (DHT), a parity system and a public blockchain to provide high resilience, assurance, scalability, and efficiency for automotive and other high-assurance systems.

Abstract The hydrocarbons constituting the heavy tail of gasoline are key contributors to particulate matter (PM) emissions from spark-ignition (SI) engines. They are predominantly aromatic and, to a significant degree, bicyclic aromatic. For example, above a boiling point of 400°F, the content of bicyclic compounds in the United States (US) summer E10 regular-grade gasoline exceeds 50%v. Various gasoline parameters, such as the PM Index, Particulate Evaluation Index (PEI), Particulate and Soot Correlation Equation (PASCE), or Threshold Sooting Index (TSI), have been proposed as predictors of PM emissions from SI engines. In particular, the PM Index, whose value is dominated by the content of heavy aromatics and which, so far, has yielded the most predictive PM emissions models, appears to be the best metric to achieve this objective.

Abstract The 2010 Environmental Protection Agency (EPA) Emission Standard for heavy-duty engines required 0.2 g/bhp-hr over certification cycles (cold and hot Federal Test Procedure [FTP]), and the California Air Resources Board (CARB) standards require 0.02 g/bhp-hr for the same cycles leading to a 90% reduction of overall oxides of nitrogen (NOx) emissions. Similar reductions may be considered by the EPA through its Cleaner Trucks Initiative program. In this article, aftertreatment system components consisting of a diesel oxidation catalyst (DOC); a selective catalytic reduction (SCR) catalyst on a diesel particulate filter (DPF), or SCR-F; a second DOC (DOC2); and a SCR along with two urea injectors have been analyzed, which could be part of an aftertreatment system that can achieve the 0.02 g/bhp-hr standard.

Abstract Heavy-duty (HD) diesel engines are the primary propulsion systems in use within the transportation sector and are subjected to stringent oxides of nitrogen (NOx) and particulate matter (PM) emission regulations. The objective of this study is to develop a robust calibration technique to optimize HD diesel engine for performance and emissions to meet current and future emissions standards during certification and real-world operations. In recent years, California - Air Resources Board (C-ARB) has initiated many studies to assess the technology road maps to achieve Ultra-Low NOx emissions for HD diesel applications [1]. Subsequently, there is also a major push for the complex real-world driving emissions as the confirmatory and certification testing procedure in Europe and Asia through the UN-ECE and ISO standards.

Abstract In this article, a novel hybrid metaheuristic based on passing vehicle search (PVS) cultural algorithm (CA) is proposed. This contribution has a twofold aim: First is to present the new hybrid PVS-CA. Second is to prove the effectiveness of the proposed algorithm for adaptive signal timing optimization. For this, a system that can adapt efficiently to the real-time traffic situation based on priority signal control is developed. Hence, Transit Signal Priority (TSP) techniques have been used to adjust signal phasing in order to serve emergency vehicles (EVs) and manage the tram priority in a coordinated tram intersection. The system used in this study provides cyclic signal operation based on a real-time control approach, including an optimization process and a database to manage the sensor data from detectors for real-time predictions of EV and tram arrival time.

Abstract The Noise, Vibration, and Harshness (NVH) performance of automotive powertrain (PT) mounts involves the PT source vibration, PT mount stiffness, road input, and overall transfer path design. Like safety, performance, and durability driving dynamics, vehicle-level NVH also plays a major contributing factor for electric vehicle (EV) refinement. This article highlights the recent research on PT mounting-related NVH controls on electric cars. This work’s main contribution lies in the comparative study of the internal combustion engine (ICE)-based PT mounting and EV-based PT mounting system (PMS) with specific EV challenges. Various literature on PT mounts from the passive, semi-active, and active mounting systems are studied. The parameter optimization technique for mount stiffness and location by various research papers is summarized to understand the existing methodologies and research gap in EV application.

Abstract Particulate matter (PM) indices—those linking PM emissions from gasoline engines to the composition and properties of the fuel—have been a topic of significant study over the last decade. It has long been known that fuel composition has a significant impact on particulate emissions from gasoline engines. Since gasoline direct injection (GDI) engines have become the market-leading technology, this has become more significant because the evaporative behavior of fuel increases in importance. Several PM indices have been developed to provide metrics describing this behavior and correlating PM emissions. In this article, 16 different PM indices are identified and collected—to the authors’ knowledge, all of the indices are available at the time of writing. The indices are reviewed and discussed in the context of the information required to calculate them, as well as their utility.

Abstract To reduce particulate emissions, the use of particulate filters in diesel engines is meanwhile state of the art, while the integration of such systems in gasoline engines is now also necessary in order to comply with today’s regulations. Over its lifetime, a gasoline particulate filter (GPF) collects ash components of fuel, lubrication oil, and materials originating from the catalytic coating and from engine abrasion. In the development and application process, synthetic ashing from GPFs is challenging. The ash of the lubrication oil can be increased in various ways, like oil-doped fuel, a separate oil burner, or changes in the piston-cylinder system of the engine. However, these methods show major disadvantages.

Abstract Particulates are a major source of emission from diesel engine. They consist of particles of carbon, sulfates, oil, fuel, and water. These constituents are measured by filtering a sample diluted in a partial- or full-flow tunnel and weighing them. It is a general trend for measuring particulate matter (PM) on cycle basis. But 1-D simulation needs complete PM 3-D contour map considering all engine operating region. It is very tedious work for generating PM on each steady-state point on engine test bed. Hence, Filter smoke meter or opacimeter measurements can be used for estimating PM. Filter smoke meters measured the light reflected from a filter paper through which a known volume of exhaust gas was passed. Opacity meters measure light absorbed by a standard column of exhaust. Both equipments measure visible black smoke comparatively at lower expenditure cost. They are designed to control measurement noise, resolution and repeatability with acceptable accuracy level.

Abstract Gasoline particulate filters (GPFs) are important aftertreatment components that enable gasoline direct injection (GDI) engines to meet European Union (EU) 6 and China 6 particulate number emissions regulations for nonvolatile particles greater than 23 nm in diameter. GPFs are rapidly becoming an integral part of the modern GDI aftertreatment system. The Active Exhaust Tuning (EXTUN) Valve is a butterfly valve placed in the tailpipe of an exhaust system that can be electronically positioned to control exhaust noise levels (decibels) under various vehicle operating conditions. This device is positioned downstream of the GPF, and variations in the tuning valve position can impact exhaust backpressures, making it difficult to monitor soot/ash accumulation or detect damage/removal of the GPF substrate. The purpose of this work is to present a unique example of subsystem control and diagnostic architecture for an exhaust system combining GPF and EXTUN.

Abstract While the hot debate keeps going about whether the internal combustion engine (ICE) will die or not, the ICE community never stopped improving the technologies that improve the fuel economy and reduce harmful emissions. Focusing on the emissions and the control system, this article reviewed the latest improvement and advances of related technologies. By firstly introducing the noteworthy emissions from ICE, this work then summarized the evolution of the related emission regulations on both light-duty and high-duty vehicles in a few major market regions. The key technologies that applied or are still under development for both carbon dioxide (CO2), nitrogen oxides (NOx), and particulate matter (PM)/particle number (PN) emissions control were reviewed in detail. Lastly, the foreseeable regulations limits and the potential challenges were discussed briefly.

Abstract In this experimental study, a novel combustion technique, “reactivity-controlled compression ignition” (RCCI), has been investigated using alcohols acting as low-reactivity fuel (LRF) and mineral diesel acting as high-reactivity fuel (HRF). Combustion experiments were performed in a single-cylinder research engine at a constant engine speed of 1500 rpm and a low engine load of 3 bar brake mean effective pressure (BMEP). RCCI combustion is a practical low-temperature combustion (LTC) concept, which was achieved using three primary alcohols: Methanol, Ethanol, and Butanol in different premixed ratios (rp = 0.25, 0.50, and 0.75) with mineral diesel. Results showed a relatively superior performance and emissions characteristics of RCCI combustion compared to conventional compression ignition (CI) combustion. The influence of LRF was visible in RCCI combustion, which exhibited a more stable combustion compared to the baseline CI combustion.

Abstract Autonomous driving faces the difficulty of securing the lowest possible software execution times to allow a safe and reliable application. One critical variable for autonomous vehicles is the latency from the detection of obstacles to the final actuation response of the vehicle, especially in the case of high-speed driving. A prerequisite for autonomy software is that it enables low execution times to achieve superhuman reaction times. This article presents an in-depth analysis of a full self-driving software stack for autonomous racing. A modular software stack especially developed for high-speed autonomous driving is used and the latency of the software is analyzed in four main autonomy modules: perception, prediction, planning, and control. With the help of a trace point measurement method, it is possible to investigate the end-to-end latency and runtimes of the individual modules.

Abstract Electric vehicles (EVs) are gaining ground more recently. New powertrains like electric and hybrid come with new noise, vibration, and harshness (NVH) issues previously unknown. A new approach to acoustic engineering is required to study NVH issues in EVs. The two primary dominant sources in an internal combustion engine (ICE) are engine noise due to combustion, and exhaust noise would not be there for EVs. EVs are less noisy, but several motor or battery cooling noises are encountered during design and validation. NVH is an indispensable part of subsystem integration in the EV powertrain. This article deals with various noise issues generally observed in EVs and their possible treatment to achieve the comfort car, satisfying customer expectations. The NVH-related problems for EVs are categorized into five categories: motor, wind, road, auxiliary, and other noises like integration. A detailed study of each category/problem type and NVH-suppression methods are discussed.

Abstract In this article, the method based on the combination of the acoustic perturbation equations and the statistical energy analysis has been used to simulate and optimize the interior aerodynamic noise of a large sport utility vehicle model. The reliability of the method was verified by comparing the analysis results with the wind tunnel test. Influenced by the main noise sources such as A-pillar, exterior rearview mirror, and front sidewindow, the wind noise of the model was significantly greater than that of the same class. To improve the wind noise performance, the side mirror was optimized with the method, including the minimum distance between the rearview mirror and the triangle trim cover, the angle between the rearview mirror and the front sidewindow, and the shell groove of the rearview mirror. The simulation results show that the overall sound pressure level in the car decreases by 2.12 dBA and the articulation index increases by 4.04% after optimization.

Abstract This study analyzes the distribution of exhaust mass pollutants emission obtained in 1,157 tests in the European driving cycle of used light-duty vehicles (LDVs). At the time of production, the tested vehicles complied with the Federal environmental requirements of the United States (USA) and were imported to Europe from North America. They included 1,109 passenger cars (PCs) and 48 light-duty trucks (LDTs), equipped with gasoline engines. In general, for measured emissions of carbon monoxide (CO), nonmethane hydrocarbons (NMHC), nitrogen oxides (NOx), and particulate matter (PM): 25% of test results for PCs do not exceed the T2B5 limits of the US Federal Standard; 43% of test results for PCs do not exceed the thresholds, designated for on-board diagnostic system (OBD) proper functioning; 45% of test results for PCs do not exceed the European Union (EU)’s former standard “Euro-5” norms.

Abstract In order to improve performance and minimize pollutant emissions in gasoline turbocharged direct-injection (GTDi) engines, different injection strategies and technologies are being investigated. The inclusion of exhaust gas recirculation (EGR) and the variation of the start of injection (SOI) are some of these strategies that can influence the air-to-fuel (AF) mixture formation and consequently in the combustion process and pollutant emissions. This paper presents a complete study of the engine performance, pollutant emissions and aftertreatment efficiency that produces the SOI variation with a fixed EGR rate in a 4-cylinder, turbocharged, gasoline direct-injection engine with 2.0 L displacement. The equipment used in this study are TSI-EEPS for particle measurement and HORIBA MEXA 1230-PM for soot measurement being HORIBA MEXA 7100-DEGR with a heated line selector the system employed for regulated gaseous emission measurement and aftertreatment evaluation.