Browse Topic: Exhaust emissions
Drum brake systems are becoming increasingly important in electric vehicles (EV) and purpose-built vehicles due to cost competitiveness and EURO-7 particulate emission regulations. Despite this trend, drum brake friction behavior remains incompletely characterized due to its dependence on multiple coupled variables: temperature history, braking conditions, and component interactions. To address this gap, this study presents a method for developing a time-series friction torque prediction model using the Mixed-effects Random Forest (MERF) machine learning framework. Time-series data collected from sensors during drum brake dynamometer tests were analyzed to identify the key variables that govern the friction torque. Significant inputs were selected through Exploratory Data Analysis (EDA), considering test-to-test variability and potential mixed effects, and were then used to train and tune the MERF model. Model performance was evaluated by comparing predicted friction torque with measured torque, and prediction error was quantified by using Mean Absolute Error (MAE) to check whether predicted model is reliable. The proposed prediction model demonstrates a high level of agreement with experimental measurements, confirming that the MERF approach can effectively capture the non-linear and transient characteristics of drum brake friction torque from time-series sensor signals. These results indicate that friction torque estimation is feasible using only sensor signals already available from conventional test instrumentation, without additional dedicated sensors. This capability is expected to support broader applications, including brake performance prediction for vehicles equipped with drum brakes and enhanced simulation of drum brake thermal performance across operating conditions.
Mehdi Ferhan said optimizing existing technology was a challenge but ultimately the right solution for Volvo to satisfy new NOx regulations. And he says he has never been bored a single day in his career as an engineer. SAE Media senior editor Chris Clonts had an exclusive opportunity at ACT 2026 to sit down with Volvo Group's senior vice president of powertrain technology, Mehdi Ferhan. The talk of the day was EPA 2027 and its new NOx emission standard. Other topics in the free-ranging conversation included BEVs, hydrogen and current opportunities for engineers. The following was edited for length and clarity.
In the race to combat climate change, scientists are developing technologies to turn carbon dioxide (CO2) into valuable fuels and chemicals. These innovations help curb greenhouse gases while providing a low-carbon fuel to power our future. As the U.S. shifts to a low-carbon economy, we need environmentally friendly fuels to power vehicles that are hard to electrify, like planes, ships and trains. Scientists are developing the technology to convert CO2 to fuel. However, this conversion requires a lot of energy and water.
The ongoing efforts for reduction of the traffic-related greenhouse gas emissions and, at the same time, the mitigation of harmful pollutant emissions from vehicle exhaust emissions are important development tasks for the entire automotive industry worldwide according to demand to provide clean and efficient products. Further tightened fleet average FE standards and ultra-low limits for exhaust emissions require the continuous development of new propulsion system types. Due to the given reluctance of the end customer and corresponding low acceptance of fully electrified vehicles, especially in the commercial vehicle segment, new and innovative topologies are needed to meet regulatory requirements and maintain the high versatility of today’s dominating solutions. For further optimization of operating conditions with enhanced fuel efficiency, the technical strategy is also determined by uplifting the attractiveness of electric driving incl. the avoidance of areas with poor ICE efficiency and as well as the coverage of emission-critical operations by electric propulsion. In this context, the support provided by an electric drive on board the vehicle in a combined drive system is becoming increasingly important. This article discusses accordingly various platform strategies for hybridized Diesel powertrains in different sectors of commercial vehicle applications and delivers a comprehensive comparative analysis of different hybrid drive concepts. Specifically, several hybrid powertrain configurations that extend an electric drive platform (hybridized BEVs), such as series and parallel-series topologies, are compared with traditional parallel hybrid powertrain topologies based on internal combustion engines (ICE). The study focuses mainly on two different cornerstone applications: a large light commercial vehicle, ranging from 3,5 to 6,5 to. and a heavy-duty long-haul truck with 40…44 to. gross vehicle weight. It evaluates the advantages in terms of CO2 emissions and Diesel fuel savings and investigates the effects on emission controls aspects. In addition to technical comparisons, the paper addresses also regulatory demands and end customer merits, assessing the integrational effort and commonalities in components with pure ICE and battery electric topologies. Furthermore, it explores the additional impact of advanced operational strategies for Hybrid Diesel powertrains, incorporating insights from innovative observations from executed hybrid technology demonstrator vehicles.
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.
Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance prediction In comparison to LR's 4,409 kg MAE (mean absolute error), 7,061 kg RMSE (root mean square error), and 0.9825 R2 value, XGBoost significantly excelled with validation results showing an R2 value of 0.9992 and an RMSE of 1,514 kg In the absence of labelled test targets, cross-validation nevertheless showed a constant degree of generalizability The residual diagnostics showed that the model was reliable for practical execution with low-variance deviations that were unbiased An accurate ATOW estimate improves the demand-capacity balance and On-Time Performance (OTP) in ATM, which in turn affects the runway schedule, wake turbulence diversion, slot allocation, and fuel planning The results highlight the need to include ATOW predictions in both tactical and strategic planning to reduce delays, increase airspace usage, and promote sustainable aviation operation and possesses significant improvements will consist of weather and runway conditions, stochastic ambiguity computation, and drift monitoring to keep up with ever-changing operating variables while maintaining accurate forecasts.
Sealing systems in space applications must perform reliably under demanding conditions in engineering: cryogenic temperatures, vibration, leakage control, ultra-high vacuum, ionizing radiation, abrasive particulates, and repeated thermal cycling. Each factor strains conventional sealing technologies. In combination, they can rapidly cause failure in systems where margins are unforgiving and maintenance is impossible. As spacecraft architectures evolve toward longer operational lifetimes and broader mission profiles, sealing requirements continue to tighten. Launch vehicles, satellites, and exploration platforms now operate across wider temperature ranges and in contact with more aggressive propellants and media. As a result, both metal seals and engineered polymer alternatives are evaluated-and selected-against increasingly specific, measurable performance criteria.
Aerospace and defense systems demand materials capable of maintaining performance under extreme environmental and operational stressors, including wide thermal cycling ranges, exposure to hydrocarbon fuels, vacuum conditions, and repeated mechanical strain. Silicone-based materials have become essential in these environments because they can retain elasticity, stability, and functionality where many traditional materials fail. Silicones are widely used as coatings, adhesives, sealants, and elastomers in aircraft and spacecraft applications. Their chemical structure enables resistance to both high and low temperatures, while also providing durability against solvents and fuels such as jet fuel. In contrast, many conventional elastomers degrade under prolonged thermal exposure or become brittle at cryogenic temperatures.
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