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One solution to the low specific power of hybrid electric vehicular batteries is a hybrid energy storage system (HESS) that takes advantage of the high specific power performance of ultra-capacitors. The design of a type of zero current transition (ZCT) soft switching bidirectional direct current-direct current (DC-DC) power converter that can be used as an ultra-capacitor-battery interface in an active parallel schema of a HESS is described. The circuit operation of the ZCT DC-DC power converter is depicted in detail. The HESS controller is designed as a two-layered hierarchical control structure: the first layer is responsible for working mode control of the HESS, and the second layer is responsible for DC-DC power converter control in which a fuzzy logic PID algorithmis employed. Simulation results indicate that this design is a potential solution to the problem of the low specific power of batteries, especially for regenerative braking and electric motor assist. The proposed active parallel schema with ZCT exhibits a significant advantage in power and energy decoupling. HESS with ZCT achieves better efficiency compared to the battery only operation. The experimental results validates the idea that the ultra-capacitor cooperates with the battery in acceleration mode. [ABSTRACT FROM AUTHOR]

The quadratic knapsack problem ( QKP) maximizes a quadratic objective function subject to a binary and linear capacity constraint. Due to its simple structure and challenging difficulty, it has been studied intensively during the last two decades. This paper first presents some global optimality conditions for ( QKP), which include necessary conditions and sufficient conditions. Then a local optimization method for ( QKP) is developed using the necessary global optimality condition. Finally a global optimization method for ( QKP) is proposed based on the sufficient global optimality condition, the local optimization method and an auxiliary function. Several numerical examples are given to illustrate the efficiency of the presented optimization methods. [ABSTRACT FROM AUTHOR]

In this paper, from a Hamiltonian point of view, the nonlinear optimal control problems are transformed into nonlinear two-point boundary value problems, and a symplectic adaptive algorithm based on the dual variational principle is proposed for solving the nonlinear two-point boundary value problem. The state and the costate variables within a time interval are approximated by using the Lagrange polynomial and the costate variables at two ends of the time interval are taken as independent variables. Then, based on the dual variational principle, the nonlinear two-point boundary value problems are replaced by a system of nonlinear equations which can preserve the symplectic structure of the nonlinear optimal control problem. Furthermore, the computational efficiency of the proposed symplectic algorithm is improved by using the adaptive multi-level iteration idea. The performance of the proposed algorithm is tested by the problems of Astrodynamics, such as the optimal orbital rendezvous problem and the optimal orbit transfer between halo orbits. [ABSTRACT FROM AUTHOR]