Towards Optimal Real-Time Automotive Emission Control
Doctoral thesis, 2021
The legal bounds on both toxic and carbon dioxide emissions from automotive vehicles are continuously being lowered, forcing manufacturers to rely on increasingly advanced methods to reduce emissions and improve fuel efficiency. Though great strides have been made to date, there is still a large potential for continued improvement. Today, many subsystems in vehicles are optimized for static operation, where subsystems in the vehicle perform well at constant operating points. Extending optimal operation to the dynamic case through the use of optimal control is one method for further improvements.
This thesis focuses on two subtopics that are crucial for implementing optimal control; dynamic modeling of vehicle subsystems, and methods for generating and evaluating computationally efficient optimal controllers. Though today's vehicles are outfitted with increasingly powerful computers, their computational performance is low compared to a conventional PC. Any controller must therefore be very computationally efficient in order to feasibly be implemented. Furthermore, a sufficiently accurate dynamic model of the subsystem is needed in order to determine the optimal control value. Though many dynamic models of the vehicle's subsystems exist, most do not fulfill the specific requirements set by optimal controllers.
This thesis comprises five papers that, together, probe some methods of implementing dynamic optimal control in real-time. Two papers develop optimal control methods, one introduces and studies a cold-start model of the three-way catalyst, one paper extends the three-way catalyst model and studies optimal cold-start control, and one considers fuel-optimally controlling the speed of the engine in a series-hybrid. By combining the method and model papers we open for the potential to reduce toxic emissions by better managing cold-starts in hybrid vehicles, as well as reducing carbon dioxide emissions by operating the engine in a more efficient manner during transients.
This thesis focuses on two subtopics that are crucial for implementing optimal control; dynamic modeling of vehicle subsystems, and methods for generating and evaluating computationally efficient optimal controllers. Though today's vehicles are outfitted with increasingly powerful computers, their computational performance is low compared to a conventional PC. Any controller must therefore be very computationally efficient in order to feasibly be implemented. Furthermore, a sufficiently accurate dynamic model of the subsystem is needed in order to determine the optimal control value. Though many dynamic models of the vehicle's subsystems exist, most do not fulfill the specific requirements set by optimal controllers.
This thesis comprises five papers that, together, probe some methods of implementing dynamic optimal control in real-time. Two papers develop optimal control methods, one introduces and studies a cold-start model of the three-way catalyst, one paper extends the three-way catalyst model and studies optimal cold-start control, and one considers fuel-optimally controlling the speed of the engine in a series-hybrid. By combining the method and model papers we open for the potential to reduce toxic emissions by better managing cold-starts in hybrid vehicles, as well as reducing carbon dioxide emissions by operating the engine in a more efficient manner during transients.
dynamic programming
optimal control methods
hybrid vehicles
three way catalyst modelling
Automotive emissions control
For password, email natasha.adler-gronbech@chalmers.se
Opponent: Assistant Professor Simona Onori, Department of Energy Resources, Stanford University, USA
Author
Jonathan Lock
Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering
A Computationally Fast Iterative Dynamic Programming Method for Optimal Control of Loosely Coupled Dynamical Systems with Different Time Scales
IFAC-PapersOnLine,;Vol. 50(2017)p. 5953-5960
Paper in proceeding
Undiscounted control policy generation for continuous-valued optimal control by approximate dynamic programming
International Journal of Control,;Vol. 95(2022)p. 2854-2864
Journal article
Optimal Transient Real-Time Engine-Generator Control in the Series-Hybrid Vehicle
ASME 2019 Dynamic Systems and Control Conference, DSCC 2019,;Vol. 2(2019)
Paper in proceeding
A Control-Oriented Spatially Resolved Thermal Model of the Three-Way-Catalyst
SAE Technical Papers,;(2021)
Paper in proceeding
Cold-Start Modeling and On-Line Optimal Control of the Three-Way Catalyst
Emission Control Science and Technology,;Vol. In press(2021)
Journal article
It is well-known that the carbon dioxide gas generated by burning fossil fuels in automobiles contributes to climate change. This is however not their only exhaust and they also generate other troublesome gases; primarily carbon monoxide, nitrogen oxides, and small amounts of partially burnt fuel. These gases in turn contribute to smog, heart and lung conditions, cancer, and other diseases. These toxic emissions are a byproduct of the combustion process and unavoidable even when non-fossil fuels are used. The Three-Way Catalyst (TWC) is one component that can be used to reduce the level of harmful emissions by converting them to non-toxic carbon dioxide, water, and nitrogen gas. The TWC has been very effectively utilized, and can under ideal conditions eliminate nearly all the emissions from gasoline engines. However, the TWC is only effective at removing these emissions when sufficiently hot. This leads to a large initial release of emissions every time the engine is started with a cold TWC.
This thesis focuses on the intersection of optimal control methods and dynamic modeling with the goal of reducing the generated emissions and consumed fuel, particularly in hybrid vehicles. This thesis introduces new variants of general optimal control methods as well as models of the dynamics found in the TWC and hybrid vehicle engines. Using these methods with the developed models allows both for constructing controllers that reduce the level of emissions generated during cold-starts as well as reducing the fuel consumption during changes in the engine's speed. The presented controllers can in the future be implemented in production vehicles, as they do not require any complex calculations to be performed.
This thesis focuses on the intersection of optimal control methods and dynamic modeling with the goal of reducing the generated emissions and consumed fuel, particularly in hybrid vehicles. This thesis introduces new variants of general optimal control methods as well as models of the dynamics found in the TWC and hybrid vehicle engines. Using these methods with the developed models allows both for constructing controllers that reduce the level of emissions generated during cold-starts as well as reducing the fuel consumption during changes in the engine's speed. The presented controllers can in the future be implemented in production vehicles, as they do not require any complex calculations to be performed.
Driving Forces
Sustainable development
Areas of Advance
Transport
Energy
Subject Categories
Energy Engineering
Computational Mathematics
Control Engineering
Signal Processing
ISBN
978-91-7905-482-3
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4949
Publisher
Chalmers
For password, email natasha.adler-gronbech@chalmers.se
Opponent: Assistant Professor Simona Onori, Department of Energy Resources, Stanford University, USA