The CO2 emissions from road vehicles must be reduced in order to avoid a 1.5 ◦C global warming. To reduce tailpipe emissions, a strong trend is to electrify powertrains to shift away from the use of fossil fuel. Among alternatives, the fuel cellhybrid electric vehicle (FCHEV) is seen as a promising configuration. With the high energy density of hydrogen propulsion systems, it is regarded viable for heavy-dutylong cycle hauling. The aim of this thesis is thus to explore optimal control of energy and thermal management systems of FCHEVs. With the intention of increasing knowledge of how to control FCHEVs for a driving mission, this thesis models an FCHEV powertrain for optimal control purposes. The developed model is used in conjunction with dynamic programming to find the hydrogen optimal control strategies of the energy and thermal management systems. Finally, a sensitivity analysis is performed, investigating how the fuel cell characteristics influence the control strategies. The results propose a feasible complete powertrain model for optimal control purposes and provides insight on how to optimally control the powertrain for various scenarios, minimizing hydrogen consumption. It is concluded that for demanding missions, the fuel cell should consistently provide the main power output and together with the battery handle power transients. For less demanding missions, the fuel cell should be controlled with an on/off strategy, switching between being atidle and working in its most efficient region. It is also concluded that integrated energy and thermal strategies for the fuel cell during a driving mission can increase fuel efficiency, with the optimal thermal strategy being dependent on the fuel cell’s characteristics.

To meet the continuously increasing goals in vehicle fuel efficiency, a number of measures are taken in automotive powertrain engineering, such as the combination of electric drives and conventional combustion engines in hybrid vehicles or the increase in gear ratios. This development leads to more complex powertrain systems, such as automatic transmissions. At the same time, the need for complex control systems is increased to achieve this desired functionality. Automatic transmissions are controlled by an electro-hydraulic control unit that governs all operations such as gear shifting and starting. Since most of the control software is designed in the form of open-loop control, most of the operations have to be calibrated manually. Thus, there exists a large number of calibration parameters in the control software that have to be tuned individually for each combination of engine, transmission and vehicle model. This process is therefore time-consuming and costly. Hence, it would be advantageous to reduce the need for calibration and in the end shorten the development process for automatic transmissions by reducing software complexity while maintaining functionality and performance. The goal of this thesis is to replace parts of the control software responsible for conducting the gearshifts that require extensive tuning by implementing control systems that have no need for calibration: adaptive high-gain λ-tracking controllers. In order to obtain the control parameters, i.e., the feedback gains, without calibration, an adaption law is implemented that continuously computes these parameters during operation of the controller. Thus, calibration is no longer needed. Since the system has to be high-gain-stabilizable, an extensive system analysis is conducted to determine whether an adaptive λ-tracking controller can be implemented. A nonlinear model of the clutch system dynamics is formulated and investigated. As a result, high-gain stability is proven for the system class and validated in simulation. Following the stability analysis, the devised adaptive controller is implemented into the control software running on the series production transmission control unit. Extensive simulations with a comprehensive vehicle model running the extended transmission software are conducted to design and to test the adaptive controllers and their underlying parameters during transmission operation in order to evaluate the control performance. The control software containing the adaptive controller is then implemented in two distinct vehicles with different automatic transmissions equipped with series production control hardware for the purpose of hardware experiments and validation. The resulting reduction of calibration efforts is discussed.

To meet the continuously increasing goals in vehicle fuel efficiency, a number of measures are taken in automotive powertrain engineering, such as the combination of electric drives and conventional combustion engines in hybrid vehicles or the increase in gear ratios. This development leads to more complex powertrain systems, such as automatic transmissions. At the same time, the need for complex control systems is increased to achieve this desired functionality. Automatic transmissions are controlled by an electro-hydraulic control unit that governs all operations such as gear shifting and starting. Since most of the control software is designed in the form of open-loop control, most of the operations have to be calibrated manually. Thus, there exists a large number of calibration parameters in the control software that have to be tuned individually for each combination of engine, transmission and vehicle model. This process is therefore time-consuming and costly. Hence, it would be advantageous to reduce the need for calibration and in the end shorten the development process for automatic transmissions by reducing software complexity while maintaining functionality and performance. The goal of this thesis is to replace parts of the control software responsible for conducting the gearshifts that require extensive tuning by implementing control systems that have no need for calibration: adaptive high-gain λ-tracking controllers. In order to obtain the control parameters, i.e., the feedback gains, without calibration, an adaption law is implemented that continuously computes these parameters during operation of the controller. Thus, calibration is no longer needed. Since the system has to be high-gain-stabilizable, an extensive system analysis is conducted to determine whether an adaptive λ-tracking controller can be implemented. A nonlinear model of the clutch system dynamics is formulated and investigated. As a result, high-gain stability is proven for the system class and validated in simulation. Following the stability analysis, the devised adaptive controller is implemented into the control software running on the series production transmission control unit. Extensive simulations with a comprehensive vehicle model running the extended transmission software are conducted to design and to test the adaptive controllers and their underlying parameters during transmission operation in order to evaluate the control performance. The control software containing the adaptive controller is then implemented in two distinct vehicles with different automatic transmissions equipped with series production control hardware for the purpose of hardware experiments and validation. The resulting reduction of calibration efforts is discussed.