Development of an Efficient Thermal Electric Skipping Strategy for the Management of a Series/Parallel Hybrid Powertrain

Abstract

In recent years, the development of hybrid powertrain allowed to substantially reduce the CO2 and pollutant emissions of vehicles. The optimal management of such power units represents a challenging task since more degrees of freedom are available compared to a conventional pure-thermal engine powertrain. The a priori knowledge of the driving mission allows identifying the actual optimal control strategy at the expense of a quite relevant computational effort. This is realized by the off-line optimization strategies, such as Pontryagin minimum principle—PMP—or dynamic programming. On the other hand, for an on-vehicle application, the driving mission is unknown, and a certain performance degradation must be expected, depending on the degree of simplification and the computational burden of the adopted control strategy. This work is focused on the development of a simplified control strategy, labeled as efficient thermal electric skipping strategy—ETESS, which presents performance similar to off-line strategies, but with a much-reduced computational effort. This is based on the alternative vehicle driving by either thermal engine or electric unit (no power-split between the power units). The ETESS is tested in a “backward-facing” vehicle simulator referring to a segment C car, fitted with a hybrid series-parallel powertrain. The reliability of the method is verified along different driving cycles, sizing, and efficiency of the power unit components and assessed with conventional control strategies. The outcomes put into evidence that ETESS gives fuel consumption close to PMP strategy, with the advantage of a drastically reduced computational time. The ETESS is extended to an online implementation by introducing an adaptative factor, resulting in performance similar to the well-assessed equivalent consumption minimization strategy, preserving the computational effort.

Integration of a Model Predictive Control with a Fast Energy Management Strategy for a Hybrid Powertrain of a Connected and Automated Vehicle

“…It is worth underlining that, differently from other methods (such as the "Rule-Based" strategies), the ETESS is versatile and also suitable to any HEV architecture. The reliability and effectiveness of ETESS have been verified in previous works along different driving cycles [6,43,44].…”

“…The MPC strategy proposed in this work acts as a high-level controller, operating as an interface between the Smart Road and a hybrid powertrain. Thus, on one side the MPC manages vehicle maneuvers acting on the steering angle and wheel torque, based on the information from the surrounding environment, considering: On the other hand, the torque request provided by MPC is handled by the EMS through the ETESS strategy proposed by the authors in previous works [5,6]. In this way, the MPC occupies two layers of the real-time control for CAVs presented in [3]: (i) motion control; (ii) powertrain control.…”

“…In this work, the EMS uses the ETESS strategy, proposed by the authors in [5,6]. ETESS aims at minimizing HEV fuel consumption, and it requires a reduced computational effort with respect to existing strategies (i.e., ECMS), such that it is more suitable to the be run on the same control unit of the MPC.…”

“…where R bat and V bat are assumed to be only function of the current SoC and P bat is the power exchanged by the battery (positive if drained from the battery). s corr evaluation is based on the mathematical function proposed in [5,6]. It is worth underlining that, differently from other methods (such as the "Rule-Based" strategies), the ETESS is versatile and also suitable to any HEV architecture.…”

“…The controller had two outputs, the steering angle of the wheels and the torque request for the powertrain. The torque request was handled by the EMS through the ETESS proposed by the authors in previous works [5,6]. The ETESS aims at minimizing the HEV fuel consumption, and it requires a reduced computational effort with respect to existing strategies (i.e., ECMS) such that it can run on the same control unit of the MPC.…”