Power Smoothing Energy Management and Its Application to a Series Hybrid Powertrain

Cairano, Stefano Di; Liang, Wei; Kolmanovsky, Ilya; Kuang, Ming; Phillips, Anastasia

doi:10.1109/tcst.2012.2218656

Cited by 95 publications

(41 citation statements)

References 26 publications

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“…This approach does not account for the transient cost of switching operating point and how to actually control the GenSet to the setpoints in an optimal manner is rarely studied. In [16,101] the assumption is that the GenSet should not deviate too far from the optimal operating line, both stationary and during the transients. In [101] this is achieved by limiting the power after the setpoint generation, whereas in [16] the possible setpoint candidates are restricted, but both solutions mean that the battery is used to compensate for the GenSet dynamics.…”

Section: Modeling and Optimal Control Of Hybrid Electric Vehiclesmentioning

confidence: 99%

“…In [16,101] the assumption is that the GenSet should not deviate too far from the optimal operating line, both stationary and during the transients. In [101] this is achieved by limiting the power after the setpoint generation, whereas in [16] the possible setpoint candidates are restricted, but both solutions mean that the battery is used to compensate for the GenSet dynamics. In [37], where a model for a turbocharged diesel GenSet is used, this leads to the engine not being able to produce the requested power, due to the time constant of the diesel engine.…”

Section: Modeling and Optimal Control Of Hybrid Electric Vehiclesmentioning

confidence: 99%

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Optimal Control of Electrified Powertrains

Sivertsson

2015

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The cover: Front: Formulation and solution of an optimal control problem, coincidentally the benchmark problem in Paper 6. Back: Positive and not so positive exit messages from the solvers used in the dissertation. Typeset with L A T E X 2εPrinted by LiU-Tryck, Linköping, Sweden 2015 i Abstract 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 b...

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Section: Modeling and Optimal Control Of Hybrid Electric Vehiclesmentioning

confidence: 99%

Section: Modeling and Optimal Control Of Hybrid Electric Vehiclesmentioning

confidence: 99%

Optimal Control of Electrified Powertrains

Sivertsson

2015

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“…Due to limited spark timing authority, the airflow-generated torque must be controlled in a range around the requested torque. In hybrid electric vehicles the combustion engine power needs to be controlled so that the difference with the driver-requested power can be achieved by electric power (Cairano et al 2013). The controller needs to track the engine speed reference.…”

Section: Introductionmentioning

confidence: 99%

Model predictive control for tracking randomly varying references

Falugi

2014

International Journal of Control

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This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyzes its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterize the set to which the tracking error converges and the associated region of convergence.

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“…For series hybrids on the other hand, where the GENSET is augmented with an energy storage, there are several publications. A common approach is to use the stationary map to generate setpoints for the GENSET, see Yoo et al [2009], Cairano et al [2012, Sezer et al [2011]. This optimization does not consider the transient effects of the GENSET and therefore raises the question if the optimal setpoint actually is the operating point with highest efficiency.…”

Section: Introductionmentioning

confidence: 99%

“…This optimization does not consider the transient effects of the GENSET and therefore raises the question if the optimal setpoint actually is the operating point with highest efficiency. Another approach is to limit the change in requested power from the GENSET so the controller can maintain the GENSET operating close to its stationary optimal line, see Cairano et al [2012], Yoo et al [2009]. This means that the energy storage needs provide a larger part of the requested power, but it also assumes that it is optimal to follow the stationary optimal line in transients.…”

Section: Introductionmentioning

confidence: 99%

Optimal and real-time control potential of a diesel-electric powertrain

Sivertsson

Eriksson

2014

IFAC Proceedings Volumes

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Real-time control strategies and their performance related to the optimal control trajectories for a diesel-electric powertrain in transient operation are studied. The considered transients are steps from idle to target power. A non-linear four state-three input mean value engine model, incorporating the important turbocharger dynamics, is used for this study. The strategies are implemented using the SAE J1939-standard for engine control and evaluated compared to both the optimal solution and the solution when the engine is restricted to follow its stationary optimal line. It is shown that with the control parameters tuned for a specific criteria both engine control strategies in the SAE J1939-standard, speed control and load control, can achieve almost optimal results, where engine load controlled shows a better trade-off between fuel economy and duration. The controllers are then extended and it is shown that it is possible to control the powertrain in a close to optimal way using the SAE J1939-standard, both with the engine speed and load controlled. However the mode where the engine is load controlled is seen to be more robust.

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Power Smoothing Energy Management and Its Application to a Series Hybrid Powertrain

Cited by 95 publications

References 26 publications

Optimal Control of Electrified Powertrains

Optimal Control of Electrified Powertrains

Model predictive control for tracking randomly varying references

Optimal and real-time control potential of a diesel-electric powertrain

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