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 consumption minimization strategy and implemented to function without any
knowledge of the future driving mission. The optimal torque distribution is calculated oine and
stored in tables. Despite only considering stationary operating conditions and average battery
parameters, the result is close to that of deterministic dynamic programming. E ects of making
the discretization of the tables sparser are also studied and found to have only minor e ects on
the fuel consumption. The controller optimizes the torque distribution for the current gear as
well as assists the driver by recommending the gear that would give the lowest consumption.
Two ways of adapting the control according to the battery state of charge are proposed and
investigated. One of the adaptive strategies is experimentally evaluated and found to ensure
charge sustenance despite poor initial values.
Martin Sivertsson, Christofer Sundström and Lars Eriksson
2011
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Last updated: 2021-11-10
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