Xiaoguo Storm
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Xiaoguo Storm has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Hoang Nguyen Khac
Aalto University
3 shared publications - Jari Hyvönen
Research and Technology Development, Marine Power Supply, Wärtsilä Finland Oy, Vaasa, Finland
3 shared publications - Kai Zenger
Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
3 shared publications - Amin Modabberian
Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, Maarintie 8, 02150 Espoo, Finland
2 shared publications
Latest Publications
- Open Access
- 31 December 2021
- Published by Walter de Gruyter GmbH in Open Engineering
- Vol. 11 (1) , 1160-1169
Model-based on-board post-injection control development for marine diesel engine
The increasing demands for reducing fuel consumption and emissions in contemporary technology solutions lead to the use of more sensors, actuators, and control applications. With this increasing engine complexity, the feedback design is complex due to the coupling between inputs and combustion parameters. To be able to design the controller systematically, model predictive control (MPC) comes to the scope because of its advantages in the design of multi-input multi-output (MIMO) systems, especially with its constraints handling ability and performance in simultaneously optimizing the engine fuel efficiency and emission reduction. Multi-injection is one of the promising techniques for achieving better engine performance. In this work, post-injection control is implemented utilizing MPC MIMO strategy with the target of exploring the possibility of reducing emissions and improving engine efficiency by controlling post-injection duration and injection timing. The workflow of the MPC controller design from control-oriented model (COM) establishing to MPC problem formation and solution methodology is discussed in this work. Moreover, one contribution from this work is the different implementation angle when compared with the state-of-the-art approaches, where the MPC controller is implemented purely by Matlab Simulink to enable the rapid control prototyping design. The simulation result demonstrated the ability of the controller's tracking performance and showed a preliminary step towards the nonlinear combustion model-based multi-injection MPC design. The systematic model-based controller framework developed in this work can be applied to other control applications and enables a fast path from design to test.
- 31 December 2021
- Published by Walter de Gruyter GmbH in Open Engineering
- Vol. 11 (1) , 1160-1169
Open AccessModel-based on-board post-injection control development for marine diesel engine
The increasing demands for reducing fuel consumption and emissions in contemporary technology solutions lead to the use of more sensors, actuators, and control applications. With this increasing engine complexity, the feedback design is complex due to the coupling between inputs and combustion parameters. To be able to design the controller systematically, model predictive control (MPC) comes to the scope because of its advantages in the design of multi-input multi-output (MIMO) systems, especially with its constraints handling ability and performance in simultaneously optimizing the engine fuel efficiency and emission reduction. Multi-injection is one of the promising techniques for achieving better engine performance. In this work, post-injection control is implemented utilizing MPC MIMO strategy with the target of exploring the possibility of reducing emissions and improving engine efficiency by controlling post-injection duration and injection timing. The workflow of the MPC controller design from control-oriented model (COM) establishing to MPC problem formation and solution methodology is discussed in this work. Moreover, one contribution from this work is the different implementation angle when compared with the state-of-the-art approaches, where the MPC controller is implemented purely by Matlab Simulink to enable the rapid control prototyping design. The simulation result demonstrated the ability of the controller's tracking performance and showed a preliminary step towards the nonlinear combustion model-based multi-injection MPC design. The systematic model-based controller framework developed in this work can be applied to other control applications and enables a fast path from design to test.
- Open Access
- 14 December 2020
- Published by Walter de Gruyter GmbH in Open Engineering
- Vol. 11 (1) , 1134-1140
Model predictive control for a multiple injection combustion model
In this work, a model predictive controller is developed for a multiple injection combustion model. A 1D engine model with three distinct injections is used to generate data for identifying the state-space representation of the engine model. This state-space model is then used to design a controller for controlling the start of injection and injected fuel mass of the post injection. These parameters are used as inputs for the engine model to control the maximum cylinder pressure and indicated mean effective pressure.
- 14 December 2020
- Published by Walter de Gruyter GmbH in Open Engineering
- Vol. 11 (1) , 1134-1140
Open AccessModel predictive control for a multiple injection combustion model
In this work, a model predictive controller is developed for a multiple injection combustion model. A 1D engine model with three distinct injections is used to generate data for identifying the state-space representation of the engine model. This state-space model is then used to design a controller for controlling the start of injection and injected fuel mass of the post injection. These parameters are used as inputs for the engine model to control the maximum cylinder pressure and indicated mean effective pressure.
- Open Access
Operational Profile Based Optimization Method for Maritime Diesel Engines
This paper presents an approach to a new engine calibration method that takes the engine’s operational profile into account. This method has two main steps: modeling and optimization. The Design of Experiments method is first conducted to model the engine’s responses such as Brake Specific Fuel Consumption (BSFC) and Nitrogen Oxide ( ) emissions as the functions of fuel injection timing, common rail pressure and charged air pressure. These response surface models are then used to minimize the fuel consumption during a year, according to a typical load profile of a ferry, and to fulfill the limits set by International Maritime Organization (IMO) regulations, Tier II, test cycle E2. The Sequential Quadratic Programming algorithm is used to solve this minimization problem. The results showed that the fuel consumption can be effectively reduced with the flexibility to trade it off with the emissions while still fulfilling the IMO regulations. In general, this method can decrease the manual calibration effort and improve the engine’s performance with a tailored setting for individual operational profiles.Open AccessOperational Profile Based Optimization Method for Maritime Diesel Engines
This paper presents an approach to a new engine calibration method that takes the engine’s operational profile into account. This method has two main steps: modeling and optimization. The Design of Experiments method is first conducted to model the engine’s responses such as Brake Specific Fuel Consumption (BSFC) and Nitrogen Oxide ( ) emissions as the functions of fuel injection timing, common rail pressure and charged air pressure. These response surface models are then used to minimize the fuel consumption during a year, according to a typical load profile of a ferry, and to fulfill the limits set by International Maritime Organization (IMO) regulations, Tier II, test cycle E2. The Sequential Quadratic Programming algorithm is used to solve this minimization problem. The results showed that the fuel consumption can be effectively reduced with the flexibility to trade it off with the emissions while still fulfilling the IMO regulations. In general, this method can decrease the manual calibration effort and improve the engine’s performance with a tailored setting for individual operational profiles.