Reviewing and updating performance measurement systems (PMS) based on internal and external environmental changes are as important as developing and implementing them. The results of an action ...research study carried out to improve the PMS of an energy company's maritime transportation area are presented. The findings of this longitudinal study illustrate the difficulty and complexity of reviewing and updating an energy company's PMS for its maritime transportation area. This difficulty is due to the involvement of PMS users, the assessment of performance measures, the establishment of targets, and data availability. The complexity is related to the changes in information technology when implementing changes in procedures for computing performance measures. This article contributes to a better understanding of the process of reviewing and updating a company's existing PMS.
► Our findings have shown the difficulty and complexity in reviewing and updating an existing PMS. ► The difficulty is related to the involvement of users of PMS, the assessment of performance measures, and data availability. ► Complexity is related to changes in information technology to implement the change in procedure for computing the measures.
Hybrid electric vehicles (HEVs) are perceived to be more energy efficient and less polluting than conventional internal combustion engine (ICE) vehicles. However, increasing evidence has shown that ...real-driving emissions (RDE) could be much higher than laboratory type approval limits and the advantages of HEVs over their conventional ICE counterparts under real-driving conditions have not been studied extensively. Therefore, this study was conducted to evaluate the real-driving fuel consumption and pollutant emissions performance of HEVs against their conventional ICE counterparts. Two pairs of hybrid and conventional gasoline vehicles of the same model were tested simultaneously in a novel convoy mode using two portable emission measurement systems (PEMSs), thus eliminating the effect of vehicle configurations, driving behaviour, road conditions and ambient environment on the performance comparison. The results showed that although real-driving fuel consumption for both hybrid and conventional vehicles were 44%–100% and 30%–82% higher than their laboratory results respectively, HEVs saved 23%–49% fuel relative to their conventional ICE counterparts. Pollutant emissions of all the tested vehicles were lower than the regulation limits. However, HEVs showed no reduction in HC emissions and consistently higher CO emissions compared to the conventional ICE vehicles. This could be caused by the frequent stops and restarts of the HEV engines, as well as the lowered exhaust gas temperature and reduced effectiveness of the oxidation catalyst. The findings therefore show that while achieving the fuel reduction target, hybridisation did not bring the expected benefits to urban air quality.
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•Two pairs of HEVs and ICE vehicles were tested in a novel convoy mode using PEMS.•Both HEVs and ICE vehicles had higher RDE fuel consumption than laboratory results.•HEVs saved 23%–49% fuel relative to their ICE counterparts in real-driving.•HEVs showed no reduction in HC and consistently higher CO compared to ICE vehicles.
This paper studies the impact of realistic wide-area measurement system (WAMS) time-varying delays on the dynamic behavior of power systems. A detailed model of WAMS delays including quasi-periodic, ...stochastic, and constant components is presented. Then, this paper discusses numerical methods to evaluate the small-signal stability as well as the time-domain simulation of power systems with inclusion of such delays. The small-signal stability analysis is shown to be able to capture the dominant modes through the combination of a characteristic matrix approximation and a Newton correction technique. A case study based on the IEEE 14-bus system compares the accuracy of the small-signal stability analysis with Monte Carlo time-domain simulations. Finally, the numerical efficiency of the proposed technique is tested through a real-world dynamic model of the all-island Irish system.
•A new online measurement system for tracking glass position changes is proposed.•A relationship between glass position changes and the measurement data is established.•The validation experimental ...setup is constructed to verify the reliability of the system.•The experiment of the ultrafast laser welding of glass and metal is conducted.
The use of ultrafast lasers to join glass and metal requires consideration of joint strength and precision, highlighting the need for an advanced measurement system. In this paper, a new online measurement scheme is proposed which uses a single camera in combination with a single autocollimator to calculate the decoupling relationship between the glass position and the observed quantity, quantify the change of the position of the pairs of welded glass in the five degrees of freedom, and analyze the factors affecting the change of the glass position through experiments.
A novel noise-cancelling readout circuit (NCRC) is proposed to improve the linearity and sensitivity of traditional voltage–time (V–T) measurement system for ruthenium dioxide (RuO2) urea biosensor. ...To reduce the non-ideal effect related to traditional V–T measurement system that negatively threatened by the impact of power line noise, this NCRC adopts a new power line noise elimination scheme. Moreover, by employing the Twin-T notch filter and the Sallen–Key low-pass filter, the proposed NCRC can increase the linearity by 161% while retaining the sensitivity at an average level than V–T measurement system. A new NCRC for measuring the linearity and sensitivity of RuO2 urea biosensor is implemented by a real circuit board. The experimental results show that the proposed NCRC can achieve 0.956 linearity and 1.22 mV/(mg/dl) average sensitivity.
The average-speed emission model (Speed-based model), a widely used and simple method of calculating road vehicle emissions, offers easy accessibility by expressing emissions as a function of average ...speed. However, there are limitations in expressing emissions generated through complex mechanisms simply as a function of speed. Real-world driving tests using a portable emission measurement system can incorporate the impact of vehicle driving load on emissions. In this study, we analyzed real-world emissions data from 94 light-duty vehicles and developed time-based emission factors depending on vehicle speed and vehicle-specific power (VSP). We also propose a speed-VSP based model to estimate regional CO2 and NOx emissions by combining time-based emission factors and vehicle operating times. The speed-based model and Speed-VSP based model exhibit a 44% difference in NOx emissions and a 29% difference in CO2 emission. In a comparison of the two models against RDE test results, the speed-VSP based model achieved high accuracy in predicting NOx and CO2 emissions with a lower root mean square error (RMSE). Specifically, for NOx emissions predictions, the speed-VSP based model achieved an RMSE of 122–270 mg/km, while the speed-based model showed a much higher RMSE of 435–476 mg/km. For CO2 emissions predictions, the speed-VSP based model achieved an RMSE of 34–56 mg/km, while the speed-based model showed a much higher RMSE of 36–72 mg/km. The results of this study present an opportunity to reassess and improve conventional method of measuring and evaluating emissions from road transport.
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•#1 Real driving emissions have established a foundation for incorporating the driving load into emission factors.•#2 Vehicle specific power is a key predictor to evaluate CO2, NOx emissions.•#3 Speed-VSP based method was proposed by combining time-based emission factors and vehicle operating times.•#4 The speed-based model and speed-VSP based method exhibit a 44% difference in NOx emissions and a 29% difference in CO2 emission.•#5 Speed-VSP based method model achieved good accuracy in predicting NOx and CO2 emissions with a lower root mean square error.
Quality control during the manufacturing process is an important factor in delivering products in electronics according to planned characteristics and properties. It concerns the capability of the ...chosen measurement system to perform precise and reliable measurement trials, which is evaluated mainly through the utilization of measurement system analysis. In order to reduce time effort and to partially automate these operations, a methodology for the prediction of a part of the dataset through applying the Neural Net algorithm is proposed in this paper in two scenarios: (1) when two metrology experts are involved in the measurement in three trials and the data of a third specialist are predicted and (2) when three metrology specialists collect data in two trials and the data of the third trial are predicted. The developed predictive models in these two scenarios are assessed and they are characterized by high accuracy. Gage repeatability and reproducibility analysis are used to evaluate the measurement systems based on original and partially artificial datasets as the comparative results outline the suitability of the proposed approach, due to the proximity of the obtained values.
Volatile organic compounds (VOCs) of motor vehicles contribute greatly to ground-level ozone formation, especially in the megacity regions. While the variations of tailpipe VOC emissions along with ...the vehicle technologies and road conditions are rarely investigated systematically. Thus, on-road tailpipe VOC emissions from in-use vehicles, including light-duty gasoline vehicles (LDGV), light-duty diesel trucks (LDDT), heavy-duty diesel truck (HDDT) and liquefied petroleum gas-electric hybrid bus (LPGB), were sampled with a combined portable emission measurement system (PEMS). A total of 102 individual VOC species were quantified by a gas chromatography mass spectrometry detector (GC-MSD), and the maximum incremental reactivity (MIR) scale was used to calculate the ozone formation potentials (OFPs). Results showed that aromatics and alkanes were the major VOC groups regardless of the vehicle type, accounting for 68.1–98.0%. For the LDGV, i-pentane, acetone, and propane were the top three VOC species. Naphthalene, dodecane and n-undecane were main VOC constituents in the diesel exhaust. Acetone was the most abundant VOC species for the LPGB, followed by i-pentane, i-butane and n-butane. Road conditions had a significant impact on the VOC emission factors. Specifically, emission factors on urban roads were 3.3–7.0 times those on the highway. The OFPs were 70.7, 128.1, 2189.4 and 124.7 mg O3/km for the LDGV, LDDT, HDDT and LPGB, respectively; aromatics were the main contributors, occupying 49.6–93.4% of the total OFPs. Results indicated that emission factors and dominant species of VOCs were strongly affected by vehicle technologies and road conditions, but aromatics were the major group for both VOC composition and OFPs.
•VOCs from various types of vehicles were investigated systematically with the PEMS.•Aromatics and alkanes were the dominant VOC groups from in-use vehicle exhaust.•Aromatics were the major contributors of the total OFPs, accounting for 49.6–93.4%.•Naphthalene was the most abundant VOC species emitted by HDDT, accounting for 31.8%.•Road conditions had great impacts on tailpipe VOC emissions.
In an interconnected multi-area power system, wide-area measurement based damping controllers are used to damp out inter-area oscillations, which jeopardize grid stability and constrain the power ...flows below to their transmission capacity. The effect of wide-area damping control (WADC) significantly depends on both power and cyber systems. At the cyber system layer, an adversary can inflict the WADC process by compromising either measurement signals, control signals or both. Stealthy and coordinated cyber-attacks may bypass the conventional cybersecurity measures to disrupt the seamless operation of WADC. This paper proposes an anomaly detection (AD) algorithm using supervised Machine Learning and a model-based logic for mitigation. The proposed AD algorithm considers measurement signals (input of WADC) and control signals (output of WADC) as input to evaluate the type of activity such as normal, perturbation (small or large signal faults), attack and perturbation-and-attack. Upon anomaly detection, the mitigation module tunes the WADC signal and sets the control status mode as either wide-area mode or local mode. The proposed anomaly detection and mitigation (ADM) module works inline with the WADC at the control center for attack detection on both measurement and control signals and eliminates the need for ADMs at the geographically distributed actuators. We consider coordinated and primitive data-integrity attack vectors such as pulse, ramp, relay-trip and replay attacks. The performance of the proposed ADM algorithms was evaluated under these attack vector scenarios on a testbed environment for 2-area 4-machine power system. The ADM module shows effective performance with 96.5% accuracy to detect anomalies.
•Real-world performance comparison between compressed natural gas and diesel buses.•Higher THC emissions for the compressed natural gas bus compared to the diesel bus.•Increase of 6–55% of fuel ...consumption with variations in the operating conditions.•Less NOx emissions for the natural gas bus at high congestion and road grade levels.•Vehicle specific power predicts CO2 and NOx emissions with good accuracy.
This study investigated the effects of passenger load, road grade, and congestion level on the fuel consumption and emissions from a Euro VI compressed natural gas (CNG) urban bus and a Euro V diesel urban bus. Testing was performed under real-traffic conditions in Madrid, Spain, using a portable emission measurement system (PEMS). The PEMS data also were combined with the vehicle specific power (VSP) methodology to analyse the differences between the performance of the two types of buses and develop an energy-based emission model. Between the empty and 4000 kg passenger load cases, the fuel consumption and CO2 emissions for the diesel bus showed a significant increase by approximately 25%. With an increase in the road grade, and congestion level, the fuel consumption and CO2 emissions of both types of buses increased, by 6–55%. Unlike in the case of the diesel bus, the NOx emissions of the CNG bus decreased by 40–50% as the level of road grade and congestion increased. At intervals of VSP ≥ 2 kW/t, NOx emission rates for the CNG bus were approximately 60% lower than those of the diesel bus. Finally, the proposed VSP-based model estimated the fuel consumption and the CO2 and NOx emission factors with relative total errors of less than 13%.
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