Browse Topic: Environmental regulations and standards
How to ensure off-highway combustion systems operate with sufficient control to meet tightening emissions standards and evolving fuel landscapes without sacrificing reliability. Off-highway equipment is being asked to do more with less. Less margin for emissions, less tolerance for downtime and less room for inefficiency, while operating under some of the most demanding duty cycles in the transport sector. Tier 4 and Tier 5 emissions standards have reshaped engine calibration strategies. Renewable diesel and biodiesel blends are entering worksites and farms at scale. At the same time, construction, mining and agricultural machines are expected to run for 20-25 years, often at sustained high load and far from service infrastructure. In this environment, combustion systems are far from being phased out.
Though the U.S. EPA has rolled back many emissions regulations surrounding the mobility industry, its HD rules remain intact, meaning manufacturers must hit the world's most stringent NOx requirement. It was clear at a panel of industry experts that the new rule was still causing confusion among operators and fleet owners. The EPA's new limits are set at 0.035 grams per horsepower-hour during normal operation, 0.050 grams at low load and 10.0 grams at idle. A panel immediately following revealed how companies have hit the tough target, which goes into effect in January of 2027.
Why precision engineering is defining confidence in next-generation internal combustion engines. In 2026, the global transport industry, and particularly the automotive industry, finds itself under competing pressures. Regulators are tightening emissions standards, with new regulations such as the EU's Euro 7 being proposed to reduce air pollution in line with net-zero ambitions. Fleet operators are managing ever-aging vehicle populations in uncertain economic conditions, and policymakers are accelerating mandates for sustainable fuels, with countries like the UK moving forward with a Zero Emission Vehicle mandate by 2035. Across passenger vehicles, commercial transport, and off-highway machinery, engineers are now tasked with delivering measurable carbon reduction using a combination of electrification, advanced internal combustion engines (ICE) and fuel innovation without compromising safety, durability or performance.
This study explores the application of reverse engineering (RE) and digital twin (DT) technology in the design and optimization of advanced powertrain systems. Traditional approaches to powertrain development often rely on legacy designs with limited adaptability to modern efficiency and emission standards. In this work, we present a methodology combining 3D scanning, computational modeling, and machine learning to reconstruct, analyze, and enhance internal combustion engines (ICEs) and electric vehicle (EV) drivetrains. By digitizing physical components through RE, we generate high-fidelity DT models that enable virtual testing, performance prediction, and iterative improvement without costly physical prototyping. Key innovations include a novel mesh refinement technique for scanned geometries and a hybrid simulation framework integrating finite element analysis (FEA) and multi-body dynamics (MBD). Our case study demonstrates a 12% increase in thermal efficiency for a retrofitted ICE and a 15% weight reduction in an EV motor housing through topology optimization. The proposed approach not only accelerates R&D cycles but also supports circular economy principles by facilitating the remanufacturing of legacy components. This work contributes to the ongoing shift toward sustainable mobility by bridging the gap between legacy engineering and next-generation powertrain innovation.
In the pursuit of achieving stringent BS VI emission standards, maintaining the efficiency of Selective Catalytic Reduction (SCR) systems is paramount, especially in vehicles operating under low duty cycles. A significant concern in such scenarios is the accumulation of urea deposits within the SCR, which can lead to detrimental push-out effects and compromised catalyst performance. This issue is particularly prevalent during low-temperature operations, where the conditions are less favorable for the effective conversion of nitrogen oxides (NOx). To address this challenge, an innovative software control system has been developed to monitor operating conditions and detect potential urea deposit faults. The software continuously evaluates parameters such as temperature and vehicle duty cycle, identifying conditions that may lead to urea crystallization within the SCR system. When unfavorable conditions are detected, the software triggers a fault alert that activates a regeneration process aimed at dissolving the accumulated urea deposits. This proactive approach not only prevents the adverse effects of urea buildup but also ensures the continued efficiency of the SCR system in reducing NOx emissions. By facilitating timely regeneration, the software enhances the operational reliability of the SCR catalyst, thereby supporting compliance with regulatory standards.
Emissions regulations, such as Euro VI, drives the Automotive industry to innovate continuously in Engine development. One significant challenge is the engine oil pumping from the crankcase into the combustion chamber, where it participates in combustion, which contributes to increased Particulate Numbers and fails to meet Euro VI emission compliance. This issue is most noticeable during engine idling and motoring conditions. During this time, a higher negative pressure difference develops between the intake manifold, which is acting above the combustion chamber and the engine crankcase. This pressure difference drives oil-laden blow-by aerosols past piston rings during the intake stroke and through the valve stem seals, allowing oil into the combustion chamber. The impact of the pressure difference between the intake manifold and crankcase was studied by varying the crankcase pressure through crankcase ventilation system. The results confirm that oil entry into the combustion chamber, contributing to combustion, occurs primarily through the piston rings, contributing to increase in Particulate Number (PN). To address this issue, it becomes necessary to introduce a mechanism that optimizes negative crankcase pressure across varying engine operating conditions. By reducing the pressure difference between the intake manifold and crankcase, this mechanism prevents oil entering the combustion chamber, thereby minimizing Particulate Number emissions and ensuring Euro VI compliance. This study focuses on the development and implementation of a negative crankcase pressure control system via the crankcase ventilation system. Through targeted optimization, it provides an effective way to control oil pumping into the combustion chamber, thereby enhancing emission control and advancing the development of cleaner Naturally Aspirated Gas engines.
The legislation of CEV Stage V emission norms has necessitated advanced Diesel Particulate Filter calibration strategies to ensure optimal performance across diverse construction equipment applications in the Indian market. Considering the various duty cycles of cranes, backhoe loaders, forklifts, compactors, graders, and other equipment, different load conditions and operational environments require a comprehensive strategy to enhance DPF efficiency, minimize regeneration frequency, and maintain compliance with emission standards. The DPF, as an after-treatment system in the exhaust layout, is essential for meeting emission standards, as it effectively traps particulate matter. Regeneration occurs periodically to burn the soot particles trapped inside the DPF through ECU management. Therefore, understanding soot loading and in-brick DPF temperature behavior across various applications is key. This paper explores the challenges in DPF calibration for CEV Stage V and provides a comprehensive approach to address these challenges, including optimizing soot loading and thermal management for different duty cycles across various applications within a unified calibration framework. The frugal Off-Highway Vehicle market expects a leaner Exhaust Gas Treatment approach, which increases the challenges of thermal management and soot loading. Additionally, the market is moving towards extracting maximum BMEP from their engines, which impacts passive regeneration and DPF thermal stability, among other parameters.
After the implementation of BS-VI emission standards, effective exhaust after-treatment has become critical in minimizing harmful emissions from diesel engines. One significant challenge is the accumulation of hydrocarbons (HC) in the Diesel Oxidation Catalyst (DOC). Certain hydrocarbons may adsorb onto the catalyst surface yet remain unreactive, leading to potential operational inefficiencies. This phenomenon necessitates the desorption of unreactive hydrocarbons to allow space for more reactive species, thereby enhancing oxidation efficiency and overall catalyst performance. The process of desorption (DeSorb) is vital to maintaining the balance of reactive hydrocarbons within the DOC. When a vehicle is idling, unburnt fuel produces hydrocarbons that accumulate in the DOC. Upon acceleration, these hydrocarbons can lead to an uncontrolled rise in temperature, resulting in DOC push-out, catalyst damage, and downstream impacts on the Diesel Particulate Filter (DPF). To mitigate these risks, a dedicated software solution has been implemented to monitor HC levels and trigger a HC desorb mode. This proactive approach initiates regeneration before hardware failure occurs, ensuring the longevity of the DOC and maintaining compliance with emission regulations. This innovative approach not only addresses immediate operational concerns but also contributes to the broader goal of sustainable automotive engineering.
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 served to identify firing patterns that minimize noise, vibration, and harshness (NVH). These patterns were subsequently validated under controlled conditions. Results showed a broader deactivation operating range and enhanced NVH characteristics. Despite accommodations for real-world NVH constraints, the flexible system delivered NOX and fuel efficiency benefits comparable to those achieved by previous work performed on this engine.
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, melting and fractures to the DPF substrate. In the occurrence of the above scenario, DPF replacement is the only option which will be an additional expense to the end user. This paper proposes a software solution to address the above issue by detecting the DTI conditions during regeneration and applying corrective actions.
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 exhaust system equipped with dual urea dosing units. By employing two controller units, we ensure compliance with On-Board Diagnostics (OBD) requirements while effectively implementing advanced software concepts. Our approach not only enhances the efficiency of NOx reduction but also provides a robust solution for high-power diesel generators, paving the way for more sustainable operations in the power sector. Furthermore, we explore the integration of real-time monitoring and adaptive control mechanisms to respond dynamically to varying load conditions and exhaust characteristics. This ensures optimal dosing of urea, enhancing the overall performance of the EATS. This study discusses the design, implementation, and performance evaluation of the proposed system, highlighting its potential to significantly lower NOx emissions while maintaining operational efficiency in high-power diesel generator applications.
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 insights on NOx sensor activity, engine warmup operations, high-risk drive cycles, and load profiles across different operation regimes. This approach significantly reduces the reliance on costly and labor-intensive physical testing with Portable Emissions Measurement Systems (PEMS) by integrating advanced analytical methods into the workflow. By leveraging high-frequency telematics data, this method enables engineers to identify failed machines in the field more efficiently. It also provides valuable insights and reasoning behind these failures, facilitating quicker and more informed decision-making. This not only enhances emission compliance monitoring but also optimizes resource allocation and reduces overall regulatory risks. In summary, the developed methods enable effective emission compliance monitoring, reduce regulatory risks, and help optimize calibration strategies by understanding customer usage patterns. These methods are scalable for various emission regulations.
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 paper aims to demonstrate a probabilistic model that captures the interactions affecting the AdBlue system's thermal behavior.
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