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To fully utilize the fuel reduction potential of a hybrid powertrain requires a careful design of the energy management control algorithms. Here a controller is created using mapbased equivalent consumption minimization strategy and implemented to function without any knowledge of the future driving mission. The optimal torque distribution is calculated offline and stored in tables. Despite only considering stationary operating conditions and average battery parameters, the result is close to that of deterministic dynamic programming. Effects of making the discretization of the tables sparser are also studied and found to have only minor effects on the fuel consumption. The controller optimizes the torque distribution for the current gear as well as assists the driver by recommending the gear that would give the lowest consumption. Two ways of adapting the control according to the battery state of charge are proposed and investigated. One of the adaptive strategies is experimentally evaluated and found to ensure charge sustenance despite poor initial values.

Eighteen patients with mediastinal involvement of Hodgkin disease were examined with magnetic resonance (MR) imaging before and during therapy to find out if size of residual masses could be predicted from the MR characteristics of the tumor at diagnosis. After the first treatment, a significant decrease in T2 values and signal intensity ratios of tumor to fat and tumor to muscle was found in all patients. There was no significant change in T1 values. The relative decrease in tumor size correlated well with signal intensity ratios and poorly with T2 values of the original tumor. No correlation with T1 values was found. The authors conclude that size of the residual mass can be predicted from the initial size of the tumor and the signal intensity ratios at diagnosis. Since the degree of low signal intensity in the tumor before treatment probably reflects the amount of fibrotic tissue, these results support the hypothesis that residual masses after treatment are remnants of the fibrotic stroma of the original tumor.

Abstract-For a realistic model of a complex system there will be thousands of possible residual generators to be used for diagnosis. Based on engineering insights of the system to be monitored, certain algebraic and dynamic properties of the residual generators may be preferred, and therefore a method for finding sequential residual generators has been developed that accounts for these properties of the residual generator candidates. It is shown that only a small fraction of all residual generator candidates fulfill fundamental requirements, and thereby proves the value of systematic methods. Further, methods are devised for utilization of the residual generators, such as initialization of dynamic residual generators. A proposed method, considering the fault excitation in the residuals using the internal form of the residuals, significantly increases the diagnosis performance. A hybrid electric vehicle is used in a simulation study for demonstration, but the methods used are general in character and provides a basis when designing diagnosis systems for other complex systems.

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