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Controlling NOx and CO2 emissions from heavy-duty diesel vehicles (HDDVs) is receiving increasing attention. Accurate measurement of HDDV NOx and CO2 emissions is the prerequisite for HDDV emission control. Vehicle emission regulations srecommend the measurement of NOx and CO2 emissions from vehicles using an emission analyzer, which is expensive and unsuitable to measure a large number of vehicles in a short time. The on-board diagnostics (OBD) data stream of HDDVs provides great convenience for calculating vehicle NOx and CO2 emissions by providing the engine fuel flow rate, NOx sensor output, and air mass flow. The calculated vehicle NOx and CO2 emissions based on the OBD data were validated by testing a heavy-duty truck's emissions on the chassis dynamometer over the CHTC-HT driving cycle, showing that the calculated NOx and CO2 emissions based on the OBD data are consistent with the measured results by the emission analyzer. The calculated vehicle fuel consumptions based on the OBD data were close to the calculated results based on the carbon balance method and the measured results by the fuel flowmeter. The experimental results show that accessing vehicle NOx and CO2 emissions based on the OBD data is a convenient and applicable method. [ABSTRACT FROM AUTHOR]

An instantaneous emission model was developed to model and predict the real driving emissions of the low-speed vehicles. The emission database used in the model was measured by using portable emission measurement system (PEMS) under actual traffic conditions in the rural area, and the characteristics of the emission data were determined in relation to the driving kinematics (speed and acceleration) of the low-speed vehicle. The input of the emission model is driving cycle, and the model requires instantaneous vehicle speed and acceleration levels as input variables and uses them to interpolate the pollutant emission rate maps to calculate the transient pollutant emission rates, which will be accumulated to calculate the total emissions released during the whole driving cycle. And the vehicle fuel consumption was determined through the carbon balance method. The model predicted the emissions and fuel consumption of an in-use low-speed vehicle type model, which agreed well with the measured data. [ABSTRACT FROM AUTHOR]

[Display omitted] • The syndicated optimization for engine-ORC combined system is conducted. • The power, bsfc, and BSNOx of combined system are improved by coupling ANN with NSGA. • The optimum injection timing, valve phases, pump and expander speeds are obtained. • The optimized BSNOx reduces 37.16%, without the deterioration of bsfc and power. Organic Rankine cycle (ORC) could compensate for the brake power loss caused by in-engine purification by recovering exhaust energy, thus achieving lower emissions and higher power output for the engine. Aimed at identifying optimum parameters that could maximize the performance of a diesel engine-ORC combined system, this study conducts a multi-objective optimization of dynamic performance, fuel consumption, and NOx emission of the combined system, considering the engine's injection timing, intake, and exhaust phases, ORC's working fluid pump speed, and expander speed as decision variables. Initially, a validated simulation model is used to study the effect of these parameters on the performance of the combined system, indicating the necessity of optimization. Subsequently, initial datasets are obtained, with the data of decision variables obtained using the D-optimum Latin hypercube sampling method and the performance indexes calculated by the simulation model. Following these initial datasets, artificial neural network (ANN) models predicting the performance of the combined system are constructed. And the power output, brake-specific fuel consumption (bsfc), and NOx emission are optimized by coupling ANN with non-dominated sorting genetic algorithm-III. Multi-objective optimization results indicate that overly reducing NOx emissions can degrade the dynamic performance and fuel efficiency of the combined system, with the degradation of 1.85% in power output and 1.89% in bsfc as a consequence of a maximum reduction of 43.79% in Brake-specific NOx (BSNOx). Prioritizing maximum power could substantially reduce fuel consumption but weaken the effectiveness of NOx reduction, with a 4.03% improvement in power output and a reduction of 3.87% and 16.48% in bsfc and BSNOx, respectively. A balanced approach considering both dynamic performance and NOx emission is the most suitable for enhancing performance with emission control in mind. This could ensure a 37.16% reduction in BSNOx, maintaining comparable power and fuel consumption. This study offers valuable insights for future advancements in engine performance. [ABSTRACT FROM AUTHOR]

On-road driving emissions of six liquefied natural gas (LNG) and diesel semi-trailer towing vehicles (STTVs) which met China Emission Standard IV and V were tested using Portable Emission Measurement System (PEMS) in northern China. Emission characteristics of these vehicles under real driving conditions were analyzed and proved that on-road emissions of heavy-duty vehicles (HDVs) were underestimated in the past. There were large differences among LNG and diesel vehicles, which also existed between China V vehicles and China IV vehicles. Emission factors showed the highest level under real driving conditions, which probably be caused by frequent acceleration, deceleration, and start-stop. NOx emission factors ranged from 2.855 to 20.939 g/km based on distance-traveled and 6.719–90.557 g/kg based on fuel consumption during whole tests, which were much higher than previous researches on chassis dynamometer. It was inferred from tests that the fuel consumption rate of the test vehicles had a strong correlation with NOx emission, and the exhaust temperature also affected the efficiency of Selected Catalytic Reduction (SCR) after-treatment system, thus changing the NOx emission greatly. THC emission factors of LNG vehicles were 2.012–10.636 g/km, which were much higher than that of diesel vehicles (0.029–0.185 g/km). Unburned CH 4 may be an important reason for this phenomenon. Further on-road emission tests, especially CH 4 emission test should be carried out in subsequent research. In addition, the Particulate Number (PN) emission factors of diesel vehicles were at a very high level during whole tests, and Diesel Particulate Filter (DPF) should be installed to reduce PN emission. Fig. Portable Emissions Measurement System for test vehicles. a) PC; b) GPS; c) weather station; d) Exhaust flow meter; e) HORIBA OBS ONE for gaseous emissions; f) PPS-M for particulate emission; g) Batteries. Unlabelled Image [ABSTRACT FROM AUTHOR]

Organic Rankine cycle (ORC) can improve engine power by recovering exhaust energy. This paper co-optimizes the engine-ORC combined system's power and NOx emission, with decision variables of the engine's excess air ratio, spark advance angle, as well as ORC's pump and expander speeds. Firstly, a simulation model of the combined system is established and validated. Then, the initial dataset is generated by the D-optimum Latin hypercube method and simulation model. The artificial neural network (ANN) prediction models of NOx emission and power are established based on these datasets. Finally, the co-optimization is conducted using the ANN prediction model and genetic algorithm. Focusing on maximizing the combined system's power results in an 18.30 % increase in power, and a significant reduction in brake-specific fuel consumption (BSFC) and brake-specific NOx (BSNOx) by 10.10 % and 71.30 %, respectively, compared to the unoptimized basis. Targeting the lowest BSNOx leads to a limited 1.20 % increase in power output; however, it results in a 19.50 % increase in BSFC. When optimizing for both system output and BSNOx, the output remains 13.5 % above the unoptimized basis. Meanwhile, up to 89.8 % of BSNOx can be eliminated with negligible deterioration in BSFC. This study could be used for engine performance enhancements. • A data-driven ANN prediction model of engine-ORC combined system is established. • ANN cooperates with GA to co-optimize Combined system's power and NOx emission. • The optimum engine and ORC parameters for the different goals are obtained. [ABSTRACT FROM AUTHOR]

PHEVs (Plug-in hybrid electric vehicles) are thought to be energy and environment friendly, while these conclusions are seldom verified during real driving tests. To evaluate PHEV real driving energy consumption, CO 2 emission, and pollutants emission, one parallel PHEV was tested under real driving condition. The results indicate that the distance-specific energy consumption of CD (charge depleting) mode, compared with the CS (charge sustaining) mode, is 45% lower for WTW (Well to Wheel) evaluation. The CD WTW CO 2 emission is 50% higher than the CS due to the electricity generation CO 2 intensity. CD and CS mode could have similar CO 2 emission when electricity CO 2 intensity reaches 397.50 g/kWh. The limited charging reduced the PHEV energy conservation by around 50%, but the WTW CO 2 emission is also reduced. Contrary to common belief, the PHEV CD mode real driving emission is underestimated, and it could be over 30 times higher than the CS mode. The deteriorated CD emission is caused by the inaccurate power demand prejudgments and frequent engine cold high-power re-start. The driving pattern comparison reveals that the deteriorated CD emission should not be a local but global concern. These results could be used for PHEV propulsion strategy optimization and test cycle design. • CD WTW energy consumption (1.39 ± 0.06 MJ/km) is 45% lower than CS (2.52 ± 0.07 MJ/km). • CD WTW CO 2 emission (228.74 ± 9.92 MJ/km) is 49% higher than CS (153.59 ± 4.51 MJ/km). • CD and CS modes get similar CO2 emission with electricity CO2 intensity at 397.5 g/kWh. • Compared to CS mode, significantly deteriorated emission under CD mode is confirmed. [ABSTRACT FROM AUTHOR]

• Hybrid vehicles' Instantaneous PN emissions were evaluated with several parameters. • Conditions with large probabilities of high instantaneous PN were identified. • GPF re-generation could increase the emission factor by a factor of five. • The pollutant-control centered strategy should be considered for hybrid vehicles. The control strategy of hybrid vehicles is mainly optimized for better fuel efficiency and hybrid electric vehicles were reported to have higher particle emissions than conventional vehicles. To assess the high instantaneous particle number (PN) emission characteristics, four hybrid electric vehicles with different technical parameters were tested under real-world driving conditions. The high instantaneous PN emission was clustered as high emission sets (HES) and HES were evaluated with the vehicle driving conditions and engine operating conditions. The results revealed that 20% of the accumulated particles are emitted within 2% of the driving time and 80% of the accumulated particles are emitted within 20% of the driving time. Most of the HES are observed at the speed lower than 60 km/h (urban speed limit), with relatively higher engine speed. HES have higher mean positive acceleration values than their RDE counterparts. But the largest acceleration doesn't represent high particle emission, because, with the electric motor, acceleration is decoupled with the engine variation. The HES could be observed at rich/lean fuel conditions, high/low state of charge, and before/after the engine is fully warmed-up depending on the vehicle's technical characteristics. Regeneration could increase the PN emission by a factor of five. Fuel-efficiency centered strategy should be combined with the pollutant-control centered strategy to achieve cleaner hybrid technology. These results could also be useful in future policies and PN emission models. [ABSTRACT FROM AUTHOR]

• To get better fuel efficiency, vehicle application scenarios must be considered. • Particles emitted during GPF regeneration could occupy 69.92%–84.81% of the total particles. • GPF regeneration brings more thin particle exposure to the public. • CLTC doesn't close the gap between laboratory tests and real driving. Many studies have found that WLTC (The Worldwide harmonized Light vehicles Test Cycles) doesn't accord well to real driving in different regions and it's necessary to develop local test cycles. China announced its local test cycle in 2019: CLTC (China light-duty vehicle test cycle). To evaluate vehicle emission under different cycles, one conventional gasoline vehicle and its hybrid counterpart were tested on the chassis dynamometer following CLTC, WLTC, and RDE (Real Driving Emission). The fuel consumption between WLTC and RDE is at the same level. While for the conventional, CLTC fuel consumption is 8.41% higher than WLTC and for the hybrid, it's 20.23% lower than WLTC. To get better vehicle fuel efficiency, vehicle application scenarios must be considered. Frequent re-start and longer warm-up time of the hybrid leads to high CO emission than the conventional. High engine speed could result in instantaneous CO spikes and with these spikes, 25% of the total CO could be emitted in less than 10 s. For the conventional, NOx emitted during engine warm-up occupied 85.39%, 87.02%, 43.06%, 31.98%, and 55.43% of the total NOx respectively for CLTC, WLTC and three RDE tests. NOx emitted from the hybrid is less than 10% of the conventional due to lower engine load and less fuel enrichment. Hybrid particle emission is under good control with the equipment of the gasoline particle filter, but the regeneration might increase thin particle exposure to the public. For most pollutants, CLTC doesn't close the gap between laboratory tests and real driving. [ABSTRACT FROM AUTHOR]