Arkiv / Teknik

Tre disputationer – Optimal control, körcyklar samt li-jon batteri

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Idag får ni tips om tre disputationer.
5 juni – Linköpings Universitet – Optimal Control of Electrified Powertrains
10 juni – Linköpings Universitet – Evaluation, Generation, and Transformation of Driving Cycles
11 juni – KTH – Thermal Aspects and Electrolyte Mass Transport in Lithium-ion Batteries
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Disputation: Optimal Control of Electrified Powertrains

Defender: Martin Sivertsson
Division: Electrical Engineering, Vehicular Systems, ISY, Linköping University
Supervisor: Lars Eriksson
Opponent: Professor Giorgio Rizzoni, OSU.
Date and Time: 2015-06-05 at 10:15
Venue: Visionen, Hus B, Linköping University
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.

Disputation: Evaluation, Generation, and Transformation of Driving Cycles

Defender: Peter Nyberg
Supervisor: Professor Lars Nielsen
Opponent: Professor Richard Stobart, Loughborough University, UK
Date and Time: 2015-06-10 at 10:15
Venue: Visionen, Hus B, Linköping University
Driving cycles are important components for evaluation and design of vehicles. They determine the focus of vehicle manufacturers, and indirectly they affect the environmental impact of vehicles since the vehicle control system is usually tuned to one or several driving cycles. Thus, the driving cycle affects the design of the vehicle since cost, fuel consumption, and emissions all depend on the driving cycle used for design. Since the existing standard driving cycles cannot keep up with the changing road infrastructure, the changing vehicle fleet composition, and the growing number of vehicles on the road, which do all cause changes in the driver behavior, the need to get new and representative driving cycles are increasing. A research question is how to generate these new driving cycles so that they are both representative and at the same time have certain equivalence properties, to make fair comparisons of the performance results. Besides generation, another possibility to get more driving cycles is to transform the existing ones into new, different, driving cycles considering equivalence constraints.
With the development of new powertrain concepts the need for evaluation will increase, and an interesting question is how to utilize new developments in dynamometer technology together with new possibilities for connecting equipment. Here a pedal robot is developed to be used in a vehicle mounted in a chassis dynamometer and the setup is used for co-simulation together with a moving base simulator that is connected with a communication line. The results show that the co-simulation can become a realistic driving experience and a viable option for dangerous tests and a complement to tests on a dedicated track or on-road tests, if improvements on the braking and the vehicle feedback to the driver are implemented.
The problem of generating representative driving cycles, with specified ex- citation at the wheels, is approached with a combined two-step method. A Markov chain approach is used to generate candidate driving cycles that are then transformed to equivalent driving cycles with respect to the mean tractive force components, which are the used measures. Using an optimization methodology the transformation of driving cycles is formulated as a nonlinear program with constraints and a cost function to minimize. The nonlinear program formulation can handle a wide range of constraints, e.g., the mean tractive force components, different power measures, or available energy for recuperation, and using the vehicle jerk as cost function gives good drivability.
In conclusion, methods for driving cycle design have been proposed where new driving cycles can either be generated from databases, or given driving cycles can be transformed to fulfill certain equivalence constraints, approaching the important problem of similar but not the same. The combination of these approaches yields a stochastic and general method to generate driving cycles with equivalence properties that can be used at several instances during the product development process of vehicles. Thus, a powerful and effective engineering tool has been developed.

Disputation: Thermal Aspects and Electrolyte Mass Transport in Lithium-ion Batteries

Defender: Henrik Lundgren
Opponent: Ann Mari Svensson, NTNU
Supervisors: Göran Lindbergh, Mårten Behm
Date and Time: 11 June at 10:00
Venue: Sal D2, Lindstedtsvägen 5, KTH, Stockholm
Temperature is one of the most important parameters for the performance, safety, and aging of lithium-ion batteries and has been linked to all main barriers for widespread commercial success of electric vehicles. The aim of this thesis is to highlight the importance of temperature effects, as well as to provide engineering tools to study these. The mass transport phenomena of the electrolyte with LiPF6 in EC:DEC was fully characterized in between 10 and 40 °C and 0.5 and 1.5 M, and all mass transport properties were found to vary strongly with temperature. A superconcentrated electrolyte with LiTFSI in ACN was also fully characterized at 25 °C, and was found to have very different properties and interactions compared to LiPF6 in EC:DEC. The benefit of using the benchmarking method termed electrolyte mass-transport resistivity (EMTR) compared to using only ionic conductivity was illustrated for several systems, including organic liquids, ionic liquids, solid polymers, gelled polymers, and electrolytes containing flame-retardant additives. TPP, a flame-retardant electrolyte additive, was evaluated using a HEV load cycle and was found to be unsuitable for high-power applications such as HEVs.
A large-format commercial battery cell with a thermal management system was characterized using both experiments and a coupled electrochemical and thermal model during a PHEV load cycle. Different thermal management strategies were evaluated using the model, but were found to have only minor effects since the limitations lie in the heat transfer of the jellyroll.