The air-fuel ratio (AFR) has direct influence on the gasoline engines' power, fuel economy and emission, but suffers from the uncertainty in fresh air and exhaust gas flow dynamics. Therefore, in this paper a AFR controller for gasoline engines is proposed, based on physical model assisted extended state predictive observer (ESPO). The fresh air mass is estimated based on the first principle model considered dual variable valve timing system and low pressure exhaust gas recirculation. For better adaptivity against operating condition variations, two self-leaning factors are embedded in the model and corrected online. Based on the self-learning model, an extended state predictive observer (ESPO) based disturbance rejection controller is designed for model inaccuracy and transport delay compensation. Simulation results show that ESPO reduces the settling time of AFR by 40.2% and 40.8% respectively, compared to the results with the conventional extended state observer (ESO) and Smith predictor in step tests of the target AFR. The deviation of AFR from the target and setting time is reduced by 5.7% and 21% respectively by using the RLS estimator in step tests of throttle position.
In this paper, a decoupling control method is proposed, for Diesel engines equipped with the variable-geometry turbine (VGT) and exhaust gas recirculation (EGR). Based on the philosophy of active disturbance rejection control (ADRC) in a backstepping structure. The outer-loop controller tracks the boost pressure ( p2 ) by manipulating the desired pre-turbine pressure ( p3 ). In the inner-loop, a multiple-input multiple-output (MIMO) ADRC control algorithm is designed for p3 and exhaust gas recirculation rate ( X EGR). To enhance the transient response, a model-based feedforward controller assisted by tracking differentiator is used. The proposed controller is validated on a high-fidelity model by compared with existing parallel single-input single output ADRC solution. Results show that the proposed method can reduce the settling time by 50% in the step response test, and reduce the integrated absolute error (IAE) of p2 and X EGR by 40% and 51%, respectively, in the FTP75 driving cycle.
Abstract Informal settlements and settlements of displaced communities (e.g., humanitarian settlements) provide crucial shelter for people, including those negatively impacted by natural hazards and human-caused crises. However, these settlements are also prone to fire as a ‘secondary incident’. This occurrence can be influenced by the use of flammable materials in the building construction and unsafe fire and electricity practices given the harsh and sudden conditions faced (along with pre-existing economic hardship). Humanitarian practitioners and agencies are increasingly recognizing the importance of addressing the fire safety problem in humanitarian settlements, with a particular focus on community evacuation. This article presents a new method to assess the safety of the areas involved and explores the use of a pedestrian simulation model (Pathfinder), to conduct evacuation analysis in an example settlement given the occurrence of a fire. The goal is to demonstrate the potential for such applications and provide a foundation from which such an application might be formalized and tested across representative scenarios. The Pathfinder tool is widely used in the fire safety community for building evacuations. It is applied here on a larger scale, although examining the same core evacuation factors. The impact of four key factors on evacuation performance is examined (i.e., density, pre-travel delays, route choice, and restricted routes), based on a case study of the community within the Kutupalong refugee camp in Cox’s Bazar, Bangladesh. Study results show that Pathfinder provides insights into evacuation outcomes during settlement fires despite the complexity involved in creating the simulation model. The results also show that the evacuation times produced were sensitive to the four conditions tested and that the prolonged evacuation times resulting from these conditions could lead to serious consequences to settlement residents, especially in cases with fast moving fires. Of course, the accuracy of such estimates is reliant on the data available and the assumptions made to configure the model. However, we have demonstrated that the simulation tool can cope with the scenarios examined and provide insights into the evacuation dynamics produced—establishing the potential of such a tool and the value of more rigorous examination.
The impact of assisted boosting technologies on the ability to maintain desired exhaust gas recirculation is investigated. Regenerative electrically assisted turbocharging is a promising technique for significantly reducing turbo lag. In addition to mitigating turbo lag, assisted boosting systems also allow fuel economy benefits through reduced pumping losses. Pumping loss reduction is achieved through optimally managing the exhaust pressure via vane position (for a variable geometry turbocharger) or waste gate position (for a waste-gated fixed geometry turbocharger). The consequent loss in exhaust turbine power, from reduced exhaust pressure, is supplemented by electrical assist power. Reduced exhaust pressure and a rapid increase in intake pressure results in a pressure differential across the high-pressure exhaust gas recirculation valve that may not support exhaust gas recirculation flow demands. Hence, a natural trade-off exists between the reduction of pumping loss and the ability to meet exhaust gas recirculation demand, as dictated by prescribed constraints on engine-out emissions. Low-pressure exhaust gas recirculation offers a potential solution that may allow the desired fuel economy improvements without sacrificing the desired exhaust gas recirculation fractions in the intake charge. In this article, we consider this problem and investigate the potential benefits of using low-pressure exhaust gas recirculation for assisted boosted systems.
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