Cold Start Emissions Research Articles

The problem of cold start emissions from vehicles

The problem of cold start emissions from vehicles

Impact of mild hydrothermal aging on kinetics of NH[formula omitted], NO, SO[formula omitted] and CO oxidation reactions on Cu/SSZ-13 catalyst

Cu/SSZ-13 is a catalyst commonly used for selective catalytic reduction (SCR) of nitrogen oxides (NOx) in diesel engine exhaust. Standard configurations are based on SCR preceded by an oxidation catalyst, however, a close-coupled SCR configuration appears relevant for upcoming regulations addressing cold-start emissions. Two often discussed ion-exchanged Cu sites in Cu/SSZ-13 are denoted ZCuOH and Z2Cu, where Z represents an Al atom in the zeolite framework. Mild hydrothermal aging (HTA) causes Cu redistribution within the catalyst; ZCuOH sites transform into more stable Z2Cu species. In this work, the effect of mild HTA on NH3, NO, SO2, and CO oxidation is studied on a commercial Cu/SSZ-13 sample. Temperature-programmed reaction experiments, performed in a lab reactor, and previously published catalyst characterization data using H2-TPR, NH3-TPD, and DRIFTS were used to build and validate a mathematical model. It couples the kinetics of the oxidation reactions with ZCuOH and Z2Cu concentration evolution during mild HTA. The model uses two distinct rate coefficients for ZCuOH and Z2Cu sites, allowing prediction of the catalyst activity during aging. The results suggest that the rate coefficients for the studied reactions on Z2Cu are effectively nil, so the observed activity in NH3, NO, SO2, and CO oxidation can be attributed solely to ZCuOH sites.

Emission Characteristics of Particle Number from Conventional Gasoline and Hybrid Vehicles

Vehicular particle number (PN) emissions have garnered increasing attention. In this study, nine light-duty vehicles, involving conventional internal combustion engine gasoline vehicles (ICEVs) and hybrid electric vehicles (HEVs), underwent testing on a chassis dynamometer to elucidate key factors influencing PN emissions. We found that with more stringent emission standards Gasoline Direct Injection (GDI) vehicles exhibited a reduction in PN emission factors. Higher PN emissions for GDI vehicles than vehicles with Multi-Port Fuel Injection (PFI) engines were observed; meanwhile, HEV showed lower PN emissions than ICEVs. PN emissions for cold start consistently exceeded warm start across vehicles with different standards and technologies. Notably, China VI HEV exhibited a substantial 19.2-fold increase in PN emissions for cold start compared to warm start. Analysis on a second-by-second basis revealed that cold-start emissions concentrated in low speed, while warm-start emissions were prominent in extra-high speed. Concerning vehicle specific power (VSP), the lowest mean PN emission rate occurred during idle conditions. PN emissions for China IV-VI ICEVs with GDI engines would increase with the increasing VSP, whereas China VI ICEVs with PFI engines and HEV with GDI engines showed varied patterns of PN emissions, especially under cold start. Our study would further facilitate formulating effective strategies for vehicular PN emissions.

Impacts of cold starts and hybrid electric vehicles on on-road vehicle emissions

Incorporating cold-start emissions from hybrid electric vehicles (HEVs) into on-road emission modeling is fundamental to accurately assess the environmental impacts aligned with their projected deployment. This study introduces a cold-start emission model, integrating travel time, dynamic emission rates, and cold-start durations by fuel type. This study further explores the anticipated spatiotemporal patterns of annual cold-start emissions. Findings indicate a reliance on gasoline for most on-road vehicles in the next decade, but vehicle electrification could reduce carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NOX) emissions by over 60% by 2035. Cold-start emissions will remain significant (67%-79% of CO, 59%-71% of HC, and 42%-54% of NOX emissions), especially on local roads. Cold-start emissions from HEVs will contribute to 14%, 25%, and 13% of total CO, HC, and NOX emissions in 2035, respectively. This study highlights the importance of accurate modeling in understanding the environmental benefits of vehicle electrification.

Co3O4 as an efficient passive NOx adsorber for emission control during cold-start of diesel engines

The Co3O4 nanoparticles, dominated by a catalytically active (110) lattice plane, were synthesized as a low-temperature NOx adsorbent to control the cold start emissions from vehicles. These nanoparticles boast a substantial quantity of active chemisorbed oxygen and lattice oxygen, which exhibited a NOx uptake capacity commensurate with Pd/SSZ-13 at 100 °C. The primary NOx release temperature falls within a temperature range of 200-350 °C, making it perfectly suitable for diesel engines. The characterization results demonstrate that chemisorbed oxygen facilitate nitro/nitrites intermediates formation, contributing to the NOx storage at 100 °C, while the nitrites begin to decompose within the 150-200 ºC range. Fortunately, lattice oxygen likely becomes involved in the activation of nitrites into more stable nitrate within this particular temperature range. The concurrent processes of nitrites decomposition and its conversion to nitrates results in a minimal NOx release between the temperatures of 150–200 °C. The nitrate formed via lattice oxygen mainly induces the NOx to be released as NO2 within a temperature range of 200–350 °C, which is advantageous in enhancing the NOx activity of downstream NH3-SCR catalysts, by boosting the fast SCR reaction pathway. Thanks to its low cost, considerable NOx absorption capacity, and optimal release temperature, Co3O4 demonstrates potential as an effective material for PNA applications.

Evaluation of thermal management technologies for fuel efficient cold-start emissions reduction in diesel engines

The ultra-low NOx emission limits for heavy and mid-duty vehicles, which are expected to be imposed in both Europe and the USA by 2027, together with the enforcement of continuous decrease in CO2 emission levels, make the need for adoption of newer technologies in the automotive industry imperative. To achieve low tailpipe NOx emissions, the accelerated warm-up of the exhaust aftertreatment system is of great importance. On the other hand, the thermal management strategies applied for this purpose result in fuel consumption penalty and consequently higher CO2 as it can be widely found in the literature. Thus, the use and optimization of advanced thermal management technologies is critical to decrease the NOx– fuel penalty trade-off on the basis of complete driving cycles. In the present work an integrated modeled-based approach is implemented by coupling advanced, predictive 1D engine, and aftertreatment simulation models which are extensively validated via dedicated experimental data. The main goal of this approach is to define and investigate multiple engine or aftertreatment-based thermal management technologies, as well as a combination of them, creating a more efficient warm-up mode for the engine. Thermal measures such as cylinder deactivation, retarded start of the main injection, late intake valve closing (Miller cycle), intake throttling, elevated idle speed, and secondary fuel injection upstream the DOC are evaluated for their effect on the exhaust system heat-up time, the fuel consumption penalty and more importantly, for their impact on the tailpipe NOx emissions calculated by this holistic simulation approach.

Prediction of cold start emissions for hybrid electric vehicles based on genetic algorithms and neural networks

The emission of hybrid electric vehicles deteriorates during cold start, and it is a cost-effective method to reduce pollutant emissions during cold start of hybrid electric vehicles through energy management strategies. The development of energy management strategies for hybrid electric vehicle requires an accurate cold-start emissions model. However, traditional cold-start emission models based on statistics and experience are difficult to achieve satisfactory prediction accuracy, and require a lot of experimental cost and time. The use of neural networks for cold start emission prediction of hybrid electric vehicles has been widely used because of its low cost and high prediction accuracy. In this paper, the genetic algorithm is used to optimize the weights and thresholds of the neural network, and a neural network cold-start emission prediction model for hybrid electric vehicles is built. We trained the neural network using the high temperature (40 °C), normal temperature (23 °C) and low temperature (−20 °C) cold start data of hybrid vehicles obtained in the World Light Vehicle Test Code (WLTC), studied the cold start prediction results under the different cold start temperature, studied the cold start prediction results under the different input parameters, studied the cold start prediction results of the neural network optimized by the genetic algorithm. Under different input parameters and cold start temperature, the GA-BP algorithm can accurately predict the emissions of carbon monoxide (CO), carbon dioxide (CO2), hydrocarbons (THC), nitrogen oxides (NOx) and particulate matter number (PN) under hybrid electric vehicles.

Analyzing the Effect of Zr, W, and V Isomorph Framework Substitution on ZSM-5 and Beta Zeolites for Their Use as Hydrocarbon Trap.

This work evaluates the effect on the adsorption and desorption kinetics of propene and toluene (used as probe molecules for vehicle cold-start emissions) of the isomorph framework substitution of Zr, W, and V on commercial ZSM-5 and beta zeolites. TG-DTA and XRD characterization data indicated that: (i) Zr does not modify the crystalline structure of the parent zeolites, (ii) W develops a new crystalline phase, and (iii) V causes the breakdown of the zeolite structure during the aging step. The CO2 and N2 adsorption data revealed that the substituted zeolites present a narrower microporosity than pristine zeolites. As a consequence of all these modifications, the modified zeolites feature different adsorption capacity and kinetics of HCs, so, different hydrocarbon trapping ability than pristine zeolites. However, a clear correlation is not observed between the changes in the porosity/acidity of zeolites and the adsorption capacity and kinetics, which depends on: (i) the zeolite (ZSM-5 or BEA), (ii) the hydrocarbon (toluene or propene), and (iii) the cation to be inserted (Zr, W, or V).

Detailed hydrocarbon speciation and particulate matter emissions during cold-start from turbocharged and naturally aspirated trucks

Cold-start emissions remain a barrier to vehicle emissions targets and the race to zero impact emissions. Current aftertreatment catalysts are highly efficient once active but struggle at lower temperatures encountered during a cold-start. Significant research can be found on controlling cold-start NOx emissions with fewer studies on the closely linked hydrocarbon (HC) and particulate matter (PM) emissions. This study provides a detailed characterization of HC and PM emissions during cold-start transients to facilitate the development of emissions control technologies for cold-start emissions reduction. To fill this knowledge gap, cumulative and time-resolved speciation of the HC composition and particulate particle size over the initial 250s of the FTP-75 drive cycle were investigated. Emissions from both a turbocharged (t-GDI) and a naturally aspirated (na-GDI) vehicle were compared to capture the range of emissions that cold-start trapping technologies might encounter across different engine architectures. While cumulative emissions were found to be similar, time-resolved measurements show HC composition and particle sizing varied during the cold-start.

Updating emission inventories for vehicular organic gases: Indications from cold-start and temperature effects on advanced technology cars

How would the organic gas emission inventories of future urban vehicles change with new features of advanced technology cars? Here, volatile organic compounds (VOCs) and intermediate volatile organic compounds (IVOCs) from a fleet of Chinese light-duty gasoline vehicles (LDGVs) were characterized by chassis dynamometer experiments to grasp the key factors affecting future inventory accuracy. Subsequently, the VOC and IVOC emissions of LDGVs in Beijing, China, from 2020 to 2035, were calculated and the spatial-temporal variations were recognized under a scenario of fleet renewal. With the tightening of emission standards (ESs), cold start contributed a larger fraction of the total unified cycle VOC emissions due to the imbalanced emission reductions between operating conditions. It took 757.47 ± 337.75 km of hot running to equal one cold-start VOC emission for the latest certified vehicles. Therefore, the future tailpipe VOC emissions would be highly dependent on discrete cold start events rather than traffic flows. By contrast, the equivalent distance was shorter and more stable for IVOCs, with an average of 8.69 ± 4.59 km across the ESs, suggesting insufficient controls. Furthermore, there were log-linear relationships between temperatures and cold-start emissions, and the gasoline direct-injection vehicles performed better adaptability under low temperatures. In the updated emission inventories, the VOC emissions were more effectively reduced than the IVOC emissions. The start emissions of VOCs were estimated to be increasingly dominant, especially in wintertime. By winter 2035, the contribution of VOC start emissions could reach 98.98 % in Beijing, while the fraction of IVOC start emissions would decrease to 59.23 %. Spatially allocation showed that the high emission regions of tailpipe organic gases from LDGVs have transferred from road networks to regions of intense human activities. Our results provide new insights into tailpipe organic gas emissions of gasoline vehicles, and can support future emission inventories and refined assessment of air quality and human health risk.

Impacts on real-world extra cold start emissions: Fuel injection, powertrain, aftertreatment and ambient temperature

Vehicles emit substantial amounts of pollutants during start periods. Engine starts mainly occur in urban areas, causing serious harm to humans. To investigate the impacts on extra cold start emissions (ECSEs), eleven China 6 vehicles with various control technologies (fuel injection, powertrain, and aftertreatment) were monitored with a portable emission measurement system (PEMS) at different temperatures. For conventional internal combustion engine vehicles (ICEVs), the average ECSEs of CO2 increased by 24%, while the average ECSEs of NOx and particle number (PN) decreased by 38% and 39%, respectively, with air conditioning (AC) on. Gasoline direct injection (GDI) vehicles had 5% lower CO2 ECSEs, but 261% higher NOx ECSEs and 318% higher PN ECSEs than port fuel injection (PFI) vehicles at 23 °C. The average PN ECSEs were significantly reduced by gasoline particle filters (GPFs). The GPF filtration efficiency was higher in GDI than PFI vehicles due to particle size distribution. Hybrid electric vehicles (HEVs) generated excessive PN extra start emissions (ESEs), resulting in a 518% increase compared to ICEVs. The start times of the GDI-engine HEV accounted for 11% of the whole test time, but the proportion of PN ESEs relative to total emissions were 23%. Linear simulation based on the decrease in ECSEs with increasing temperature underestimated the PN ECSEs from PFI and GDI vehicles by 39% and 21%, respectively. For ICEVs, CO ECSEs varied with temperature in a U shape with a minimum at 27 °C; NOx ECSEs decreased as ambient temperature increased; PFI vehicles generated more PN ECSEs at 32 °C than GDI vehicles, stressing the significance of ECSEs at high temperature. These results are useful for improving emission models and assessing air pollution exposure in urban aeras.

Reducing Cold-Start Emissions by Microwave-Based Catalyst Heating: Simulation Studies

Reducing Cold-Start Emissions by Microwave-Based Catalyst Heating: Simulation Studies

The synergy between substrate architecture of 3D-printed catalytic converters and hydrogen for low-temperature aftertreatment systems

This study proposes 3D-printed diamond-based lattice substrates as catalytic converters in the automotive aftertreatment system to improve vehicle cold-start emissions. The study aimed to compare the influence of 3D-printed diamond-based catalyst structures on the light-off behaviour compared to the conventional 400 Cell Per Square Inch (CPSI) honeycomb catalyst design in a real exhaust gas environment. Moreover, the benefits of H2 addition on the performance of advanced lattice structures are examined for the first time to further increase the low-temperature catalytic efficiency. Digital Light Processing (DLP) technology was effectively utilised to manufacture lattice structures with high cell density to allow a comparison between conventional and advanced geometry designs. Further, the 3D-printed substrates were catalyst coated, and their light-off behaviour was studied in a diesel exhaust environment. The results of the light-off showed a significant improvement in the light-off temperatures for CO, THC and NO in the 3D-printed lattice structures. Furthermore, H2 presence additionally enhanced the low-temperature activity of the AM lattice structures.

An Experimental and Computational Study on Triple Injection Strategies to Reduce Cold Start Diesel Engine Emissions

Abstract The effect of triple injection strategies in a diesel engine to reduce cold start emissions were experimentally and computationally investigated in this work. The experiments were performed using a 1.9 L four-cylinder, turbocharged compression ignition engine with diesel fuel. As a representative of the cold start condition in the diesel engine, a low load condition of 1500 rpm and 2 bar brake mean effective pressure (BMEP) was chosen as the fixed condition for this study. The injection strategy made use of a late post injection to reduce catalyst light-off time. The pilot and main injections are fixed and the post injection timing is swept later into the expansion stroke to increase exhaust enthalpy available to heat the aftertreatment system. To further understand the source of hydrocarbon (HC) emissions from late injections, equivalent experiments were conducted with a mixture of n-heptane and iso-octane that matched the reactivity of the diesel fuel. The mixture of primary reference fuels (i.e., PRF 34) obtained by matching the cetane number (CN) of diesel fuel, showed similar combustion characteristics of diesel, but is much more volatile due to lighter components in the PRF mixture. The increased volatility of PRF 34 suppressed liquid fuel impingement on the cylinder liner, which isolated liner impingement as a possible source of HC emissions. Simulations were also performed for the present engine configuration and operating conditions in a sector mesh using CONVERGE™. The physical properties of diesel fuel were modeled using a five-component surrogate. The chemical kinetics of the diesel fuel were modeled with a reduced n-heptane model. The simulations were able to capture the experimental trends of combustion characteristics and emissions. The HC emissions were observed to increase for both fuels with retarded post injection timings in engine experiments. PRF 34 had comparable HC emissions to diesel experiments, which indicated that the liner impingement is not the main source of the increase in HC emissions. Overmixing of the fuel and air was identified as the major cause of increase in HC emissions. Additionally, exhaust gas recirculation (EGR) also intensified the overmixing phenomenon and thereby increase in HC emissions.

Thermal management of catalytic converter with heat pipe embedded in thermal energy storage to reduce cold start emissions

ABSTRACT The Thermal Energy Storage (TES) System aids in improving the cold start efficiency of the catalytic converter (CC). To further improve the TES and CC performance, loop heat pipes embedded into the PCM, TES unit are presented. For evaluation, three cases are considered: Case 1; CC without TES, Case 2; CC with TES, Case 3; CC with a heat pipe embedded in PCM TES. Mg70Zn24.9Al5.1 is used as PCM and paraffin oil as the working fluid for the heat pipe. Three 30 minute transient cycles with idle events in between were run, with the engine soaking for 30 minutes at ambient conditions with varied loads (0 to 100%) at 2000 rpm. Heat storage and release cycles were run for each load condition. Average warm-up HC, NOx and CO conversion efficiency improvement of 45–85% with Case 3, 35–62% with Case 2 compared to Case 1 were observed. Heat storage time was observed to be lower by ~ 35% for Case 3 while the heat retention time was observed to be better for Case 2 by ~44%. System efficiency and effectiveness were found to be better up to 14% and ~0.2 with Case 3 compared to Case 2. Overall Case 3 showed better performance with some penalty on the heat retention time compared Case 2.

The impact of Cold-start emissions on air pollution exposure during active travel

In emissions modeling, emissions released during cold starts are often underestimated, especially at the network level. This study quantifies the impact of cold-start emissions on human exposure during active travel (i.e., walking and bicycling) and while waiting at bus stops during the morning peak hour. Cold-start emissions of carbon monoxide (CO) are found to account for 90.2% and 77.9% of emissions on local roads and minor arterials. Neglecting cold-start emissions leads to an 82.0% underestimation of emissions at the network level. The results show that CO exposures are underestimated by 82.1%, 67.1%, and 88.8% for travelers walking, bicycling, and waiting at bus stops, respectively, when cold-start emissions are not considered. This study examines the significant contribution of cold-start emissions and recommends taking these into account in emissions modeling. The findings concerning active travelers indicate the need for a re-assessment of potential bias when neglecting cold-start emissions.

Evaluating Different Strategies to Minimize cold-start Emissions from Gasoline Engines in steady-state and Transient Regimes

Evaluating Different Strategies to Minimize cold-start Emissions from Gasoline Engines in steady-state and Transient Regimes

Evaluation of Advanced Diesel Particulate Filter Concepts for Post Euro VI Heavy-Duty Diesel Applications

The European Commission (EC) is in the process of finalizing the proposal for the upcoming legislative stage for light- and heavy-duty vehicles. The emission performance over extended operating conditions is under consideration. Furthermore, a tightening of the Solid Particle Number (SPN) limits with a parallel shift of the lowest detectable size from 23 to 10 nm has been suggested. This paper investigates the SPN emission performance of a Euro VI step E HDV and the potential offered by an advanced Diesel Particulate Filter (DPF) to meet the upcoming regulations. Cold start emissions at clean DPF state were found to be as high as 1.3 × 1012 #/kWh, while passive regeneration events could lead to hot start emissions of 3 × 1011 #/kWh. Improvements in the filtration efficiencies at clean state, similar to those offered by the advanced DPF (>99%), will be needed to tackle these operating conditions. The measurements also revealed the formation of 10 nm SPN in the Selective Catalytic Reduction (SCR) system, at a rate of ~1.2 × 1011 #/kWh. These levels lie above the proposed limit of 1011 #/kWh, highlighting the need to also control these non-volatile nanosized particles.

Comprehensive Control Strategy of Fuel Consumption and Emissions Incorporating the Catalyst Temperature for PHEVs Based on DRL

PHEVs (plug-in hybrid electric vehicles) equipped with diesel engines have multiple model transitions in the driving cycle for their particular structure. The high frequency of start–stop of a diesel engine will increase fuel consumption and reduce the catalytic efficiency of SCR (Selective Catalyst Reduction) catalysts, which will increase cold start emissions. For comprehensive optimization of fuel consumption and emissions, an optimal control strategy of PHEVs that originated from the PER-TD3 algorithm based on DRL (deep reinforcement learning) is proposed in this paper. The priority of samples is assigned with greater sampling weight for high learning efficiency. Experimental results are compared with those of the DP (dynamic programming)-based strategy in HIL (hardware in loop) equipment. The engine fuel consumption and NOX emissions were 2.477 L/100 km and 0.2008 g/km, nearly 94.1% and 90.1% of those of the DP-based control strategy. By contrast, the fuel consumption and NOx of DDPG (Deep Deterministic Policy Gradient)-based and TD3(Twin Delayed Deep Deterministic Policy Gradient) -based control strategy were 2.557, 0.2078, 2.509, and 0.2023, respectively. By comparative results, we can see that the comprehensive control strategy of PHEVs based on the PER-TD3 algorithm we proposed can achieve better performance with comparison to TD3-based and DDPG-based, which is the state-of-the-art strategy in DRL. The HIL-based experimental results prove the effectiveness and real-time potential of the proposed control strategy.

A bottom-up modeling approach to quantify cold start emissions from urban road traffic

Cold start emissions, which are released during the first minutes of driving after the vehicle engine is started, may contribute significantly to the urban road traffic emissions. Implementation of bottom-up approaches for emission quantification in urban context is crucial to address the distribution of pollution with fine temporal and spatial resolution and to establish local mitigation measures and plans. In this research a modeling approach to quantify cold start excess emissions from road transport with fine spatial resolution is proposed and applied. In combination with transportation modeling, a new module has been developed to estimate cold start emissions at road segment level and for a trip, while preserving information on Origin-Destination of the trips contributing to those emissions. The methodology was applied to Coimbra case study allowing spatial analysis of cold start emissions in the urban context. The frequency distribution and summary statistics for road segments are provided focusing on different types of roads and seasonal variations. High contribution of cold start emissions is demonstrated with median values above 70% for carbon monoxide and hydrocarbons at local roads, where most people leave or work. The methodology applied in this work highlights the importance of cold start emission quantification for traffic pollution studies.