Comparisons of STRETCH meat grinders based on two different topologies of ICCOS

Inductive energy storage systems （IES）require opening switches which are technically much more difficult to realize than closing switches. Institute of Advanced Technology （ IAT ） puts forward a meat grinder with an inductive pulse power topology called slow transfer of energy through capacitive hybrid （STRETCH）. In this topology, an integrated gate-commutated thyristor （IGCT） is capable of breaking the charging currents on the order of 4 kA, and it may encounter difficulties in expanding to higher energy systems. German-French Institute of Saint Louis （ISL） has developed a high-power opening switch based on standard high-power thyristors by using their so-called inverse current commutation with semiconductor devices （ICCOS） countercurrent commutation principle. Two topologies of the STRETCH meat grinder with ICCOS are analyzed. And they are compared based on the voltage across the main switch, the current multiplication factor and other aspects by u- sing Matlab simulations. The advantages and disadvantages of the two topologies are shown through the comparisons. Therefore a more suitable topology can be chosen for realistic applications accord- ing to their performances.

New self-calibration schemes for accelerometers in platform INS

To ensure success of precise navigation, it is necessary to carry out in-field calibration for the accelerometers in platform inertial navigation system(PINS) before a mission is launched.Traditional continuous self-calibration methods are not fit for fast calibration of accelerometers because the platform misalignments have to be estimated precisely and the nonlinear coupling terms will affect accuracy. The multi-position methods with a "shape of motion" algorithm also have some existing disadvantages: High precision calibration results cannot be obtained when the accelerometer's output data are used directly and it is difficult to optimize the calibration scheme. Focusing on this field, this paper proposes new fast self-calibration methods for the accelerometers of PINS. A data compression filter is employed to improve the accuracy of parameter estimation because it is impossible to obtain non-biased estimation for accelerometer parameters when using the "shape of motion" algorithm. Besides, continuous calibration schemes are designed and optimized by the genetic algorithm(GA) to improve the observability of parameters. Simulations prove that the proposed methods can estimate the accelerometer parameter more precisely than traditional continuous methods and multi-position methods, and they are more practical to deal with urgent situations than multi-position methods.