Martin Sivertsson

Adaptive Control of a Hybrid Powertrain with Map-based ECMS

To fully utilize the fuel reduction potential of a hybrid powertrain requires a careful design of the energy management control algorithms. Here a controller is created using mapbased equivalent co ...

Time and Fuel Optimal Power Response of a Diesel-Electric Powertrain

Optimal control policies for a diesel-electric powertrain in transient operation are studied. In order to fully utilize the extra degree of freedom available in a diesel-electric powertrain, compar ...

Adaptive Control Using Map-Based ECMS for a PHEV

A plug-in hybrid electric vehicle(PHEV) is a promising way of achieving the benets of the electric vehicle without being limited by the electric range. This paper develops an adaptive control strategy based on a map-based ECMS approach. The control is developed and implemented in a simulator provided by IFP Energies nouvelles for the PHEV benchmark. The implemented control strives to be as blended as possible, whilst still ensuring that all electric energy is used in the driving mission. The controller is adaptive to reduce the importance of correct initial values but since the initial values aect the consumption a method is developed to estimate the optimal initial value for the controller based on driving cycle information. This is seen to work well for most driving cycles with promising consumption results. The controller also fullls all requirements set by the PHEV Benchmark. A hybrid electric vehicle(HEV) utilizes both electric en- ergy and energy from fuel to meet the demands set by the driver. This may lead to a reduction in environmental impact and fuel consumption of the vehicle. A Plug-In HEV(PHEV) is a HEV with possibility to recharge the battery from the grid. This adds the potential of using the vehicle as an electric vehicle, without the range limitations in a pure electric vehicle. The supervisory control algo- rithm for these more complex powertrains play an impor- tant role in realizing the full potential of the powertrain. In order to evaluate dierent

Optimal Transient Control Trajectories in Diesel–Electric Systems—Part I: Modeling, Problem Formulation, and Engine Properties

Vehicle powertrain electrification, i.e. combining the internal combustion engine (ICE) with an electric motor (EM), is a potential way of meeting the increased demands for efficient and low emission transportation, at a price of increased powertrain complexity since more degrees of freedom (DoF) have been introduced. Optimal control is used in a series of studies of how to best exploit the additional DoFs.In a diesel-electric powertrain the absence of a secondary energy storage and mechanical connection between the ICE and the wheels means that all electricity used by the EMs needs to be produced simultaneously by the ICE, whose rotational speed is a DoF. This in combination with the relatively slow dynamics of the turbocharger in the ICE puts high requirements on good transient control. In optimal control studies, accurate models with good extrapolation properties are needed. For this aim two nonlinear physics based models are developed and made available that fulfill these requirements, these are also smooth in the region of interest, to enable gradient based optimization techniques. Using optimal control and one of the developed models, the turbocharger dynamics are shown to have a strong impact on how to control the powertrain and neglecting these can lead to erroneous estimates both in the response of the powertrain as well as how the powertrain should be controlled. Also the objective, whether time or fuel is to be minimized, influences the engine speed-torque path to be used, even though it is shown that the time optimal solution is almost fuel optimal. To increase the freedom of the powertrain control, a small energy storage can be added to assist in the transients. This is shown to be especially useful to decrease the response time of the powertrain, but the manner it is used, depends on the time horizon of the optimal control problem.The resulting optimal control solutions are for certain cases oscillatory when stationary controls would have been expected. This is shown to be neither an artifact of the discretization used nor a result of the modeling assumptions used. Instead it is for the formulated problems actually optimal to use periodic control in certain stationary operating points. Measurements show that the pumping torque is different depending on whether the controls are periodic or constant despite the same average value. Whether this is beneficial or not depends on the operating point and control frequency, but can be predicted using optimal periodic control theory.In hybrid electric vehicles (HEV) the size of the energy storage reduces the impact of poor transient control, since the battery can compensate for the slower dynamics of the ICE. For HEVs the problem instead is how and when to use the battery to ensure good fuel economy. An adaptive map-based equivalent consumption minimization strategy controller using battery state of charge for feedback control is designed and tested in a real vehicle with good results, even when the controller is started with poor initial values. In a plug-in HEV (PHEV) the battery is even larger, enabling all-electric drive, making it it desirable to use the energy in the battery during the driving mission. A controller is designed and implemented for a PHEV Benchmark and is shown to perform well even for unknown driving cycles, requiring a minimum of future knowledge.

Optimal Transient Control and Effects of a Small Energy Storage for a Diesel-Electric Powertrain

Abstract Optimal control of a diesel-electric powertrain in transient operation as well as effects of adding a small energy storage to assist in the transients is studied. Two different types of problems are solved, minimum fuel and minimum time, with and without an extra energy storage. In the optimization both the output power and engine speed are free variables. For this aim a 4-state mean value engine model is used together with a model for the generator losses as well as the losses of the energy storage. The considered transients are steps from idle to target power with different requirements on produced energy, used as a measure on the freedom in the optimization before the requested power has to be met. For minimum fuel transients the energy storage remains unused for all requested energies, for minimum time it does not. The minimum time solution is found to both minimize the response time of the powertrain and also provide good fuel economy. For larger requested energies with energy storage the response time is immediate, with an energy storage of only 10-20Wh.

Computing Optimal Heat Release Rates in Combustion Engines

The combustion process has a high impact on the engine efficiency, and in the search for efficient engines it is of interest to study the combustion. Optimization and optimal control theory is used ...

Optimal Transient Control Trajectories in Diesel–Electric Systems—Part II: Generator and Energy Storage Effects

Vehicle powertrain electrification, i.e. combining the internal combustion engine (ICE) with an electric motor (EM), is a potential way of meeting the increased demands for efficient and low emission transportation, at a price of increased powertrain complexity since more degrees of freedom (DoF) have been introduced. Optimal control is used in a series of studies of how to best exploit the additional DoFs.In a diesel-electric powertrain the absence of a secondary energy storage and mechanical connection between the ICE and the wheels means that all electricity used by the EMs needs to be produced simultaneously by the ICE, whose rotational speed is a DoF. This in combination with the relatively slow dynamics of the turbocharger in the ICE puts high requirements on good transient control. In optimal control studies, accurate models with good extrapolation properties are needed. For this aim two nonlinear physics based models are developed and made available that fulfill these requirements, these are also smooth in the region of interest, to enable gradient based optimization techniques. Using optimal control and one of the developed models, the turbocharger dynamics are shown to have a strong impact on how to control the powertrain and neglecting these can lead to erroneous estimates both in the response of the powertrain as well as how the powertrain should be controlled. Also the objective, whether time or fuel is to be minimized, influences the engine speed-torque path to be used, even though it is shown that the time optimal solution is almost fuel optimal. To increase the freedom of the powertrain control, a small energy storage can be added to assist in the transients. This is shown to be especially useful to decrease the response time of the powertrain, but the manner it is used, depends on the time horizon of the optimal control problem.The resulting optimal control solutions are for certain cases oscillatory when stationary controls would have been expected. This is shown to be neither an artifact of the discretization used nor a result of the modeling assumptions used. Instead it is for the formulated problems actually optimal to use periodic control in certain stationary operating points. Measurements show that the pumping torque is different depending on whether the controls are periodic or constant despite the same average value. Whether this is beneficial or not depends on the operating point and control frequency, but can be predicted using optimal periodic control theory.In hybrid electric vehicles (HEV) the size of the energy storage reduces the impact of poor transient control, since the battery can compensate for the slower dynamics of the ICE. For HEVs the problem instead is how and when to use the battery to ensure good fuel economy. An adaptive map-based equivalent consumption minimization strategy controller using battery state of charge for feedback control is designed and tested in a real vehicle with good results, even when the controller is started with poor initial values. In a plug-in HEV (PHEV) the battery is even larger, enabling all-electric drive, making it it desirable to use the energy in the battery during the driving mission. A controller is designed and implemented for a PHEV Benchmark and is shown to perform well even for unknown driving cycles, requiring a minimum of future knowledge.

Optimal stationary control of diesel engines using periodic control

Measurements and optimal control are used to study whether the fuel economy of a diesel engine can be improved through periodic control of the wastegate, illustrating how modern optimal control tools can be used to identify non-trivial solutions that can improve performance. The measurements show that the pumping torque of the engine is changed when the wastegate is controlled in a periodic manner versus stationary even if the mean position is the same. If this decreases the fuel consumption or not is seen to be frequency and operating point dependent. The measurements indicate that the phenomenon occurs in the time scales capturable by mean value engine models (MVEM). The operating points are further analyzed using a MVEM and optimal control. It is shown that whether the optimal solution exhibits periodic oscillations or not is operating point dependent, but is not due to the instantaneous nature of the controls. Even if an actuator model is added the oscillations persist for reasonable time constants, the frequency of the oscillations is however affected. Further it is shown that the periodic control can be predicted by optimal periodic control theory and that the frequency of the control affects the resulting efficiency.

Turbocharger Dynamics Influence on Optimal Control of Diesel Engine Powered Systems

The importance of including turbocharger dynamics in diesel engine models are studied, especially when optimization techniques are to be used to derive the optimal controls. This is done for two ap ...

Generator Effects on the Optimal Control of a Power Assisted Diesel-Electric Powertrain

Optimal control of a diesel-electric powertrain in transient operation is studied. The attention is on how generator limits affect the solution, as well as how the addition of a small energy storage can assist in the transients. Two different types of problems are solved, minimum fuel and minimum time, with different generator limits as well as with and without an extra energy storage. In the optimization both the output power and engine speed are free variables. For this aim a 4-state mean value engine model is used together with models for the generator and energy storage losses. The considered transients are steps from idle to target power with different amounts of freedom, defined as requirements on produced energy, before the requested power has to be met. For minimum fuel transients the energy storage remains virtually unused for all requested energies, for minimum time it does not. The generator limits are found to have the biggest impact on the fuel economy, whereas an energy storage could significantly reduce the response time.