Browse Topic: Environmental regulations and standards
Anticipated NOX emission standards will require that selective catalytic reduction (SCR) systems sustain exhaust temperatures of 200°C or higher for effective conversion performance. Maintaining these temperatures becomes challenging during low-load conditions such as idling, deceleration, and coasting, which lower exhaust heat and must be addressed in both regulatory test cycles and day-to-day operation. Cylinder deactivation (CDA) has proven effective in elevating exhaust temperatures while also reducing fuel consumption. This study investigates a flexible 6-cylinder CDA system capable of operating across any combination of fixed firing modes and dynamic skip-firing patterns, where cylinders transition between activation states nearly cycle-by-cycle. This operational flexibility extends the CDA usable range beyond prior implementations. Data was primarily collected from a test cell engine equipped with the dynamic CDA system, while a matching engine in a 2018 long-haul sleeper cab
In-Use emission compliance regulations globally mandate that machines meet emission standards in the field, beyond dyno certification. For engine manufacturers, understanding emission compliance risks early is crucial for technology selection, calibration strategies, and validation routines. This study focuses on developing analytical and statistical methods for emission compliance risk assessment using Fleet Intelligence Data, which includes high-frequency telematics data from over 500K machines, reporting more than 1000 measures at 1Hz frequency. Traditional analytical methods are inadequate for handling such big data, necessitating advanced methods. We developed data pipelines to query measures from the Enterprise Data Lake (A Structured Data storage system), address big data challenges, and ensure data quality. Regulatory requirements were translated into software logic and applied to pre-processed data for emission compliance assessment. The resulting reports provide actionable
In the power industry, high-power Diesel Generator (DG) sets often utilize high power V-engine cylinder configurations to enhance power output within a compact design, ensuring smoother operation and reduced vibration. In this V-engine configurations, the exhaust gas mass flow rate is significantly higher compared to inline engines of similar displacement, due to the greater number of cylinders operating in a compact space, which leads to a higher volume of exhaust gases expelled in a shorter duration. This necessitates the use of a dual Exhaust After Treatment System (EATS) to effectively manage NOx emissions. High-power gensets typically emit NOx levels around 9 g/kWh, presenting significant challenges for developers in adhering to stringent emission standards. To address these challenges and meet CPCB IV+ emission norms, we propose a dual urea dosing system integrated with a novel control strategy aimed at optimizing the treatment of exhaust gases. This paper introduces a dual
The current and upcoming Internal Combustion Engine (ICE) emission norms are very stringent. It is difficult to meet emission standards with just combustion optimization techniques. As a result, post-treatment is required for Engine-out emissions. Otherwise, these hazardous gases impact the ecosystem of living beings. Many technologies are implemented at the exhaust for reducing the emissions. Diesel Particulate Filter (DPF) is one such technique to achieve lower Particulate Matter (PM) and Particulate Number (PN) emission goals. In order to achieve such emission reduction, the DPF undergoes periodic cleaning called regeneration. During regeneration, the exhaust systems including DPF are maintained at elevated temperatures to achieve proper cleaning. When the vehicle is in regeneration, sudden braking or accelerator pedal release leads to engine Drop to Idle speeds (DTI), which sharply increases the temperature gradient inside the DPF which may result in physical damage like cracks
In Diesel engine exhaust after treatment system (ATS), Nitrogen Oxides (NOx) emissions control is achieved via Selective Catalytic Reduction (SCR) in which AdBlue or Diesel Exhaust Fluid (DEF) plays vital role. But AdBlue freezes below -11°C due to which in cold climate conditions system performance becomes critical as it affects efficiency as well as overall performance leading to safety and compliance with emission standards issue. So, it is essential to have a probabilistic thermal model which can predict the AdBlue temperature as per ambient temperature conditions. The present paper focuses on developing Bayesian Network (BN) based algorithm for AdBlue system by modelling probability of key factors influencing on its performance including AdBlue temperature, Ambient temperature, Coolant temperature, Coolant flow, Vehicle operating conditions etc. The BN Model predicts and ensures continuous learning and improvement of the system, based on operational data. Methodology proposed in
The effective reduction of particulate emissions from modern vehicles has shifted the focus toward emissions from tire wear, brake wear, road surface wear, and re-suspended particulate emissions. To meet future EU air quality standards and even stricter WHO targets for PM2.5, a reduction in non-exhaust particulate (NEP) emissions seems to be essential. For this reason, the EURO 7 emissions regulation contains limits for PM and PN emissions from brakes and tire abrasion. Graz University of Technology develops test methods, simulation tools and evaluates technologies for the reduction of brake wear particles and is involved in and leads several international research projects on this topic. The results are applied in emission models such as HBEFA (Handbook on Emission Factors). In this paper, we present our brake emission simulation approach, which calculates the power at the wheels and mechanical brakes, as well as corresponding rotational speeds for vehicles using longitudinal dynamics
How Cummins used modeling and other advanced design software to create its most efficient engines yet. As AI and other deep-learning tools begin to help shape the transportation industry, they also bring improvements to existing technology. Modeling and simulation software has rapidly become a crucial tool for improving the design process of new diesel engines. More than two decades after the first X15 engines rolled off the assembly line, Cummins has applied today's modeling tools to help create the HELM version of the X15. The HELM architecture (which stands for Higher Efficiency, Lower emissions and Multiple fuels) is the company's basis for a global platform capable of meeting all manners of emissions regulations while still serving customers across a wide variety of use cases.
Cummins has expanded its Centum diesel generator series that elevates sustained performance while maximizing power density. The latest addition to the company's portfolio is a 17-liter engine platform that can provide up to one megawatt of power. “The S17 is engineered to redefine what you expect from an emergency standby package,” said Emily Scheuerell, Cummins power generation global engineering leader. According to Cummins, the S17 was a clean-sheet design that supports HVO (hydrotreated vegetable oil) fuel flexibility and complies with EPA Tier 2, UL2200 and CSA 22.2 emissions standards.
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