The ubiquitous influence of fossil fuels in driving the world economy and the imperative need to reduce dependence of transportation on these fuels, has brought about a decade of research on alternative propulsion systems. Of the several alternative propulsion systems, hybrid electric vehicles (HEVs) are seen as an important short-term solution. In the most generic sense, a HEV consists of a battery and one or more electric machines in addition to the engine powered by petroleum/diesel. Depending on the vehicle architecture, the additional degree of freedom in selecting the amount of energy supplied by the primary
and the secondary source of energy is a challenging control and optimization problem. The energy management strategy in a HEV aims at finding the optimal distribution of energy between the battery and the fuel to satisfy the requested power from the driver.Different energy management strategies have been developed both by the industry and the academia and they can be classified into non-realizable and realizable energy management strategies
based on the amount of information required for real-time implementation. Traditionally, the non-realizable strategies formulate the energy management problem as a constrained optimal control problem of minimizing a performance index over a finite time interval under operational constraints. These strategies provide the global optimal solution and are used as benchmark solutions for comparative analysis of strategies. The realizable strategies in the literature have been primarily developed for implementation in real vehicles and have been shown to produce results similar to the global optimal solution. In spite of the
extensive amount of research on both non-realizable and realizable energy management strategies, there are many shortcomings in the literature which have been addressed in this dissertation.
The energy management problem of finding the optimal split between the different sources of energy in a charge-sustaining pre-transmission parallel HEV, ensuring stability and optimality with respect to a performance objective, is addressed in this dissertation. The dissertation develops a generic stability and optimality framework within which energy management strategies can be analyzed and designed. The energy management problem is
cast in the form of a nonlinear optimal regulation (with disturbance rejection) problem and a control Lyapunov function is used to design the control law. A series of theorems ensuring
optimality and asymptotic stability of the energy management strategy are proposed and proved. The theorems use an appropriate Willans line model of the engine fuel consumption rate and a zero-th order model of the battery state of charge/energy dynamics. The sufficient conditions for optimality and stability are used to derive an analytical expression for the control law as a function of the battery state of charge/state of energy error, engine fuel consumption model and battery model parameters.
In this dissertation, several non-realizable and realizable energy management strategies are developed and implemented in the backward and forward vehicle simulators. The optimal control law (OCL) proposed in this dissertation is compared against dynamic programming (DP) and a version of equivalent consumption minimization strategy (ECMS) based on Pontryagin’s minimum principle. The OCL strategy is further modified to develop a realizable strategy (called real-time OCL) and its performance is compared with an adaptive version of ECMS using a forward vehicle simulator. Throughout the dissertation, the performance of the proposed strategy is evaluated against the global optimal solution from DP. The significant contribution of the dissertation is in developing and easy to implement strategy that has very less calibration effort. Though the framework and the strategy has been presented for a pre-transmission parallel HEV, it is scalable to different vehicle architectures and component sizes. The dissertation also presents a comprehensive comparison of the different proposed and developed energy management strategies.