Holistic Optimization of Energy Consumption of a Hybrid Powertrain with an “Equivalent Fuel Consumption Minimization Strategy” Algorithm

Modern hybrid powertrains consist of several energy storage and energy converters and allow multiple operating modes to propel a vehicle. In the context of energy management these operating modes are crucial for the consumption of fossil fuel and the recuperation of kinetic energy. A supervisory control strategy is mandatory to meet the driver expectations and to control the energy flow in an efficient manner. Their applicability should cover all possible driving maneuvers, respect component limits and minimize fossil fuel consumption. The “Equivalent Consumption Minimization Strategy” algorithm, as a local optimal control strategy, is derived from literature and applied to a holistic system simulation model of a hybrid powertrain and a thermal management system in the form of an embedded supervisory controller. The objective is to minimize fossil fuel consumption and to include the response dynamics and the thermal effects of the underlying components and subsystems. A special attention is given to the formulation of the cost function which includes three modifications to the well-known [1] equivalent consumption equation. The derived optimal control strategy and the simulation results of the system model are discussed regarding their applicability and the resulting energy economy to an a priori known maneuver. The proposed modifications and extensions prove their applicability in the virtual test environment and recommend themselves for the utilization in further application areas.