Stochastic stability for a model representing the intake manifold pressure of an automotive engine

The paper presents conditions to assure stochastic stability for a nonlinear model. The proposed model is used to represent the input-output dynamics of the angle of aperture of the throttle valve (input) and the manifold absolute pressure (output) in an automotive spark-ignition engine. The automotive model is second moment stable, as stated by the theoretical result—data collected from real-time experiments supports this finding.Peer ReviewedPostprint (author's final draft

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Compound cycle engine for helicopter application

The compound cycle engine (CCE) is a highly turbocharged, power-compounded, ultra-high-power-density, lightweight diesel engine. The turbomachinery is similar to a moderate-pressure-ratio, free-power-turbine gas turbine engine and the diesel core is high speed and a low compression ratio. This engine is considered a potential candidate for future military helicopter applications. Cycle thermodynamic specific fuel consumption (SFC) and engine weight analyses performed to establish general engine operating parameters and configurations are presented. An extensive performance and weight analysis based on a typical 2-hour helicopter (+30 minute reserve) mission determined final conceptual engine design. With this mission, CCE performance was compared to that of a contemporary gas turbine engine. The CCE had a 31 percent lower-fuel consumption and resulted in a 16 percent reduction in engine plus fuel and fuel tank weight. Design SFC of the CCE is 0.33 lb/hp-hr and installed wet weight is 0.43 lb/hp. The major technology development areas required for the CCE are identified and briefly discussed

Adaptive Observer for Nonlinearly Parameterised Hammerstein System with Sensor Delay – Applied to Ship Emissions Reduction

Taking offspring in a problem of ship emission reduction by exhaust gas recirculation control for large diesel engines, an underlying generic estimation challenge is formulated as a problem of joint state and parameter estimation for a class of multiple-input single-output Hammerstein systems with first order dynamics, sensor delay and a bounded time-varying parameter in the nonlinear part. The paper suggests a novel scheme for this estimation problem that guarantees exponential convergence to an interval that depends on the sensitivity of the system. The system is allowed to be nonlinear parameterized and time dependent, which are characteristics of the industrial problem we study. The approach requires the input nonlinearity to be a sector nonlinearity in the time-varying parameter. Salient features of the approach include simplicity of design and implementation. The efficacy of the adaptive observer is shown on simulated cases, on tests with a large diesel engine on test bed and on tests with a container vessel

Flexible and robust control of heavy duty diesel engine airpath using data driven disturbance observers and GPR models

Diesel engine airpath control is crucial for modern engine development due to increasingly stringent emission regulations. This thesis aims to develop and validate a exible and robust control approach to this problem for speci cally heavy-duty engines. It focuses on estimation and control algorithms that are implementable to the current and next generation commercial electronic control units (ECU). To this end, targeting the control units in service, a data driven disturbance observer (DOB) is developed and applied for mass air ow (MAF) and manifold absolute pressure (MAP) tracking control via exhaust gas recirculation (EGR) valve and variable geometry turbine (VGT) vane. Its performance bene ts are demonstrated on the physical engine model for concept evaluation. The proposed DOB integrated with a discrete-time sliding mode controller is applied to the serial level engine control unit. Real engine performance is validated with the legal emission test cycle (WHTC - World Harmonized Transient Cycle) for heavy-duty engines and comparison with a commercially available controller is performed, and far better tracking results are obtained. Further studies are conducted in order to utilize capabilities of the next generation control units. Gaussian process regression (GPR) models are popular in automotive industry especially for emissions modeling but have not found widespread applications in airpath control yet. This thesis presents a GPR modeling of diesel engine airpath components as well as controller designs and their applications based on the developed models. Proposed GPR based feedforward and feedback controllers are validated with available physical engine models and the results have been very promisin

Examining How Federal Infrastructure Policy Could Help Mitigate and Adapt to Climate Change: Hearing Before the H. Comm. on Transp. & Infrastructure, 116th Cong., Feb. 26, 2019 (Statement of Vicki Arroyo)

As the Fourth National Climate Assessment, released in November, describes, the United States is already experiencing serious impacts of climate change—and the risks to communities all across the country are growing rapidly. These findings, along with those in the 2018 Intergovernmental Panel on Climate Change (IPCC)report, are clear and should be a call to immediate action. Even if we manage to limit planetary warming to just 2 degrees C, the world will still face increased chances of economic and social upheaval from more severe flooding, droughts, heatwaves, and other climate impacts as well as devastating environmental consequences, the IPCC report warns. The scientific consensus as described in the IPCC Special Report is that countries around the world must rapidly decarbonize their economies, cutting greenhouse gas emissions in half by 2030 and to near zero by 2050. Yet the current trends are going in the wrong direction. Despite our increasing understanding of the narrowing window to act, U.S. GHG emissions increased by 3.4% in 2018, according to a January report from the Rhodium Group. Clearly more action is needed. The encouraging news is that many states and cities have committed to taking action. They are taking steps to reduce emissions through legislation, executive orders, and pledges made in collaborations such as the US Climate Alliance –now covering roughly half the US population and GDP. In my testimony, I will be focusing on the transportation sector, which is the largest contributor of GHG emissions in the United States, and is already facing significant impacts from climate change. Federal standards have been important in increasing efficiency and reducing emissions, yet transportation-sector emissions are increasing as more vehicle miles are driven, more freight is transported in trucks, and airline travel continues to grow. Transportation is becoming an increasingly large share of U.S. economy-wide emissions as the power sector decarbonizes as a result of market shifts and policy. There is an urgent need, therefore, to transition to a low-carbon transportation system. Such a transition would not only reduce emissions and fight climate change, it also would bring additional important benefits, including protecting public health by reducing conventional air pollution, providing more mobility options, and driving innovation and economic growth through policy action and through public and private investment

Actuator Fault Diagnosis with Application to a Diesel Engine Testbed

This work addresses the issues of actuator fault detection and isolation for diesel engines. We are particularly interested in faults affecting the exhaust gas recirculation (EGR) and the variable geometry turbocharger (VGT) actuator valves. A bank of observer-based residuals is designed using a nonlinear mean value model of diesel engines. Each residual on the proposed scheme is based on a nonlinear unknown input observer and designed to be insensitive to only one fault. By using this scheme, each actuator fault can be easily isolated since only one residual goes to zero while the others do not. A decision algorithm based on multi-CUSUM is used. The performances of the proposed approach are shown through a real application to a Caterpillar 3126b engine

Transient modelling of a diesel engine and air-path control

Due to the inherent nonlinearity of the diesel engine, real-time control of the variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR) valve still remains a challenging task. A controller has to be capable of coping with the transient operating condition of the engine, the interactions between the VGT and EGR, and also the trade-off effect in this control problem. In this work, novel real-time fuzzy logic controllers (RFLC) were developed and tested. Firstly, the proposed controllers were calibrated and validated in a transient diesel engine model which was developed and validated against the Caterpillar 3126B engine test bed located at the University of Sussex. The controllers were then further tested on the engine test bed. Compared to conventional controllers, the proposed controllers can effectively reduce engine emissions as well as fuel consumption. Experimental results show that compared to the baseline engine running on the Nonroad Transient Cycle (NRTC), mean values of the exhaust gas opacity and the nitrogen oxides (NOx) emission production were reduced by 36.8% and 33%, respectively. Instant specific fuel consumption of the RFLC engine was also reduced by up to 50% compared to the baseline engine during the test. Moreover, the proposed fuzzy logic controllers can also reduce development time and cost by avoiding extensive engine mapping of inlet air pressure and flow. When on-line emission measurements were not available, on-board emission predictors were developed and tested to supply the proposed fuzzy logic controller with predictions of soot and NOx production. Alternatively, adaptive neuro fuzzy inference system (ANFIS) controllers, which can learn from fuzzy logic controllers, were developed and tested. In the end, the proposed fuzzy logic controllers were compared with PI controllers using the transient engine model