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Input- and output-split hybrids using a single planetary gear (PG) can provide high fuel economy, but they tend to suffer from low acceleration performance. In order to improve their acceleration performance, speed reduction (multiplication) gears (SRG/SMG) have often been employed in various mass-produced split hybrids. In fact, adding one SRG (SMG) to input- or output-split hybrids can improve not only the acceleration performance, but also the fuel economy. Nevertheless, the full potentials of using SRGs (SMGs) have not yet been thoroughly investigated because the design space of input- and output-split configurations using one SRG (SMG) is huge; 432 configurations can be generated using two PGs where one PG is used as an SRG/SMG. Thus, in order to investigate the impacts of SRG (SMG) within a reasonable time, an efficient analysis procedure is required.

Finding optimal split hybrid configurations through exhaustive search is almost intractable, mainly due to the huge design space, e.g. 252 compound split configurations using two planetary gear sets (PG). Thus, a systematic exhaustive design methodology is required to find optimal configurations. While most of the prior studies proposed methodologies that assess the performance within the physical design space, i.e. based on the powertrain configurations, this paper proposes a compound lever-based comprehensive design methodology. The (virtual) compound lever is an attractive design tool defined by two design variables, i.e. α and β, that omits the redundancy existing within the physical design space, thus, reduces the computational load. The proposed method explores the entire (virtual) compound lever design space to find optimal compound split configurations with outstanding fuel economy and acceleration performance.

Engine start-stop system is one of the main mechanisms for fuel saving in hybrid electric vehicles (HEVs). During those transient events, especially during engine starts, the engine torque pulsations can be an NVH issue if there is direct mechanical coupling between the engine and the driveline. In addition, engine starts may also result in the interruption of driving torque. The fast torque response of the electric machines provides a possible solution to mitigate the output torque fluctuation. But the effect is limited by the capability of these two electric machines due to the three missions they must satisfy simultaneously, i.e., starting the engine, compensating the torque pulsations and providing the demanded driving torque. To thoroughly understand this problem and propose possible solutions, in this study, we developed an input-split HEV powertrain model with a grounding clutch.

This paper presents an adaptation method of equivalent factor in equivalent consumption minimization strategy (ECMS) of fuel cell hybrid electric vehicle (FCHEV) using hilly road information. Instantaneous optimization approach such as ECMS is one of real-time controllers. Furthermore, it is widely accepted that ECMS achieves near-optimum results with the selection of the appropriate equivalent factor. However, a lack of hilly road information no longer guarantees near-optimum results as well as charge-sustaining of ECMS under hilly road conditions. In this paper, first, an optimal control problem is formulated to derive ECMS analytical solution based on simplified models. Then, we proposed updating method of equivalent factor based on sensitivity analysis. The proposed method tries to mimic the globally optimal equivalent factor trajectory extracted from dynamic programming solutions.

This study investigates how hilly road profiles affect the optimal energy management strategy for fuel cell hybrid electric vehicle (FCHEV) with various battery sizes. First, a simplified FCHEV model is developed to describe power and energy flows throughout the powertrain and evaluate hydrogen consumption. Then, an optimal control problem is formulated to find the globally optimal energy management strategy of FCHEV over driving cycles with road elevation profile. In order to solve the optimal energy management problem of the FCHEV, Dynamic Programming, a dynamic optimization method, is used, and their results are analyzed to find out how hilly road conditions affect the optimal energy management strategies. The results show that the optimal energy management with a smaller battery tends to actively prepare (e.g. pre-charge/pre-discharge) for uphill/downhill roads in order not to violate the battery state of charge (SoC) bounds.