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As a key component of high‐performance switches and routers, the packet forwarding engine (PFE) is mainly responsible for selecting the appropriate output port for tens of thousands of packets within an extremely short time frame. However, the performance of PFE is determined by the selected group membership algorithm. This paper puts forth a hybrid strategy–caching scalar‐pair and vectors routing and forwarding (CSVRF), consisting of virtual output port bitmap caching (VOPBC) and fractional‐N SVRF to address major multicast forwarding issues such as scalability by using content addressable memory. In CSVRF, a virtual output port bitmap cache is introduced, which includes the most popular combinations of output port bitmap and divides the big scalar‐pair into N sub‐groups to achieve parallel compute and the reusability of less bit‐length prime. The results demonstrate that the memory space and the forwarding latency are effectively reduced compared with previous work. In space efficiency, it only required 10% memory space compared with the original SVRF/fractional‐N SVRF, decreased 10% memory usage compared with pure VOPBC and nearly improved 1 to 4 orders of magnitude of packet processing time compared with the original SVRF and the fractional‐N SVRF respectively. [ABSTRACT FROM AUTHOR]

This paper presents a novel active power control scheme for SRMs that are used as S/G units at MEAs; the proposed method uses a vector-controlled SAF, facilitating the acceleration of the SRM during starter mode and the efficient power control of the SRG at various operational points during generator mode. Moreover, an energy storage unit is incorporated in the SAF, aiming at enhancing the SRM's starting torque production and taking full advantage of the SRG's energy generation capability, through the appropriate phases’ magnetization regulation that is imposed by the developed adaptive SAF vector control. In addition, the proposed scheme provides enhanced FRTC during both modes of operation. The mathematical analysis is verified through MATLAB/Simulink simulations, while the performance of the S/G concept under study is evaluated via real-time CHIL tests, with the use of the dSPACE 1202 (MicroLabBox) platform and the 16-bit dsPIC30F4011 microcontroller. [ABSTRACT FROM AUTHOR]

High-performance multicast-enabled packet forwarding engines (PFEs), as an essential component of high-end switches, use a polynomial-time membership query algorithm to determine which port(s) the data packet should be forwarded. The currently widely used query algorithm is Bloom Filter (BF), which has been proven to have many fatal flaws. Another error-free membership query algorithm includes Scalar-pair Vectors Routing Forwarding (SVRF), Fractional-N Scalar-pair Vectors Routing Forwarding (Frac-N SVRF), and the Per-Port Prime Filter Array (P3FA) also have some shortcomings in space and time efficiencies. In this paper, we proposed a hybrid strategy: Divaricate Heterogeneous SVRF (DH-SVRF) scheme, which based on the P3FA and Frac-N SVRF, which randomly divides all member ships into N groups, and each group has the same structure and is independent of each other to obtain higher time efficiency and space utilization. Finally, we also discussed the selection of the optimal egress-diversity threshold. Through mathematical modeling and simulation, we validate that the proposed DH-SVRF scheme is superior to the SVRF/Frac-N SVRF and traditional BF in terms of scalability, space utilization, and time efficiency in specific conditions such as appropriate egress-diversity thresholds. [ABSTRACT FROM AUTHOR]

This paper presents a self-learning strategy to control the deactivation of cylinders in large displacement automotive engines. Cylinder deactivation is a useful strategy to reduce emissions and improve fuel consumption without limiting the maximum engine power. A cylinder deactivation algorithm has to balance the target of reducing emissions with drivability concerns. Changing the cylinder configuration at the wrong time or too often negatively affects drivability and fuel efficiency. The paper proposes a self-learning algorithm inspired by the Markov Chain formalism. The proposed algorithm predicts the future fuel consumption and determines the best cylinder configuration based on that prediction. The prediction algorithm is learnt online using past inputs and thus adapts to the specific driver and conditions. Two versions of the algorithm are proposed that use two different inputs. The approaches are validated in simulation on an engine test-bed, showing that the self-learning algorithm yields fuel savings up to 10% without affecting drivability in the New European Driving Cycle. [ABSTRACT FROM AUTHOR]

In this paper, the configuration of a novel plug-in hybrid electric vehicle (PHEV) system is proposed. For the novel PHEV system, the main operating modes and the control strategy, including rules for mode switching and energy management, are established. A backward model of the vehicle involving the power sources, transmission, and control system is worked out in MATLAB/Simulink/Stateflow environment. The distribution of operating points of each power source, as well as the fuel consumptions of the vehicle under new European driving cycle (NEDC) and FTP75 testing cycles are simulated and compared with typical hybrid systems such as parallel, series, and Toyota hybrid system (THS). The results indicate that the proposed system can operate at high fuel economy by adopting the rule-based energy management strategy along with the equivalent consumption minimization strategy, which proves the feasibility and effectiveness of the configuration and control strategies. [ABSTRACT FROM AUTHOR]

This paper focuses on the research of simulation model and experiment of a novel energy storage system (ESS). This novel ESS is dedicated to supplying power flow effectively for a new type of linear engine, which is used in alternative energy vehicle firstly. The control strategy has been proposed based on the ESS model, which adopts bidirectional four modes of operation to control the power flow. To sufficiently discuss the ESS dynamic behavior, the performance of the novel ESS is analyzed using simulations based on MATLAB/Simulink and experiments based on digital signal processor TMS320F2812. Finally, simulation and experimental results have verified the effectiveness of the novel ESS and the accuracy of the control strategy. [ABSTRACT FROM AUTHOR]

Dragonfly topologies are gathering great interest nowadays as one of the most promising interconnect options for High-Performance Computing (HPC) systems. However, Dragonflies contain physical cycles that may lead to traffic deadlocks unless the routing algorithm prevents them properly. In general, existing deadlock-free routing algorithms, either deterministic or adaptive, proposed for Dragonflies, use Virtual Channels (VCs) to prevent cyclic dependencies. However, these topology-aware algorithms are difficult to implement, or even unfeasible, in systems based on the InfiniBand (IB) architecture, which is nowadays the most widely used network technology in HPC systems. This is due to some limitations in the IB specification, specifically regarding the way Virtual Lanes (VLs), which are considered as similar to VCs, can be assigned to traffic flows. Indeed, none of the routing engines currently available in the official releases of the IB control software has been specifically proposed for Dragonflies. In this paper, we present a new deterministic, minimal-path routing for Dragonfly that prevents deadlocks using VLs according to the IB specification, so that it can be straightforwardly implemented in IB-based networks. We have called this proposal D3R (Deterministic Deadlock-free Dragonfly Routing). Specifically, D3R maps each route to a single, specific VL depending on the destination group, and according to a specific order, so that cyclic dependencies (so deadlocks) are prevented. D3R is scalable as it requires only 2 VLs to prevent deadlocks regardless of network size, i.e., fewer VLs than the required by the deadlock-free routing engines available in IB that are suitable for Dragonflies. Alternatively, D3R achieves higher throughput if an additional VL is used to reduce internal contention in the Dragonfly groups. We have implemented D3R as a new routing engine in OpenSM, the control software including the subnet manager in IB. We have evaluated D3R by means of simulation and by experiments performed in a real IB-based cluster, the results showing that, in general, D3R outperforms other routing engines. [ABSTRACT FROM PUBLISHER]

In the pursuit of fuel economy improvement and emission reduction, a trajectory optimization-based engine multioperating-point control strategy is proposed in this paper for the auxiliary power unit (APU) in an extended range electric vehicle. This strategy design deeply considers the transient process of the operating point switching that somehow influences the engine fuel economy and emission, and was often ignored. First, a combined cost MAP fully integrating several indices, including fuel consumption rate, CO, HC, and NOx emissions, is presented to synthetically evaluate the effect of the operation trajectory. Then an improved genetic algorithm, in terms of computational load reduction and convergence improvement, is employed to optimize the engine trajectory in the transient operating point switching process of the APU system, so that it is able to perform with the best fuel consumption and emissions. Finally, simulated and experimental results indicate that the proposed control strategy has obvious improvements in fuel economy and emissions, compared with conventional ones. [ABSTRACT FROM AUTHOR]

In this paper, a bidirectional dc-dc converter is proposed for the automotive engine/battery hybrid power generators. The two-stage bidirectional converter employing a fixed-frequency series loaded resonant converter is designed to be capable of operating under zero-current-switching turn-on and turn-off regardless of voltage and load variation, and hence its magnetic components and EMI filters can be optimized. Also, a new autonomous and seamless bidirectional voltage control method that combines two individual controllers for low-voltage side control and high-voltage side control by introducing a variable current limiter is proposed to provide uninterrupted power to critical ac loads and reduce the size of the dc bus capacitor and the transition time. Experimental results from a 5-kW prototype are provided to validate the proposed concept. [ABSTRACT FROM AUTHOR]

This paper designs and implements an expert system adopting a newly proposed adaptive load transfer strategy and inference methodology as an integrated problem-solving solution of determining an appropriate load transfer strategy when diverse events occur in a distribution system under heavy load or severe overload conditions. In particular, to enhance the efficiency of search, the proposed inference engine is designed so that a solution for the load balancing and a solution for the minimization of the outage load can be inferred at the same time by searching the goal nodes and the fail nodes based on the local minimum tree search method. [ABSTRACT FROM AUTHOR]

Fuel consumption of traditional ground vehicles is significantly affected by how the vehicles are driven. This paper focuses on the servo-loop control design of a Pulse-and-Gliding (PnG) strategy to minimize fuel consumption in automated car following. A switching-based framework is proposed for real-time implementation. The corresponding controller was synthesized for ideal conditions and subsequently enhanced to compensate for practical factors such as powertrain dynamics, speed variations, and plant uncertainties. Simulations in both uniform and naturalistic traffic flows demonstrate that, compared with a linear quadratic (LQ)-based benchmark controller, the PnG controller improves fuel economy up to 20%. The significant fuel saving is achieved while maintaining precise range bounds so that the negative impact on safety/traffic flow is contained. The developed algorithm can potentially be embedded in adaptive cruise control systems to achieve fuel-saving function. [ABSTRACT FROM PUBLISHER]

Experience developing and deploying model-based diagnosis (MBD) and recovery and other model-based technologies on a variety of testbeds and flight experiments led us to explore why our expectations about the impact of MBD on spacecraft operations have not been matched by effective benefits in the field. By MBD, we mean the problem of observing a mechanical, software, or other system and determining what failures its internal components have suffered using a generic inference algorithm and a model of the system's components and interconnections. These techniques are very attractive, suggesting a vision of machines that repair themselves, reduced costs for all kinds of endeavors, spacecraft that continue their missions even when failing, and so on. This promise inspired a broad range of activities, including our involvement over several years in flying the Livingstone and L2 onboard MBD and recovery systems as experiments on Deep Space 1 and Earth Observer 1 spacecraft. Yet, in the end, no spacecraft project adopted the technology in operations nor flew additional flight experiments. To our knowledge, no spacecraft project has adopted any other MBD technology in operations. In this paper, we present a cost/benefit analysis for MBD using expectations and experiences with Livingstone as an example. We provide an overview of common techniques for making spacecraft robust, citing fault protection schemes from recent missions. We lay out the cost, benefit, and risk advantages associated with onboard MBD and use the examples to probe each expected advantage in turn. We suggest a method for evaluating a mission that has already been flown and providing a rough estimate of the maximum value that a perfect onboard diagnosis and recovery system would have provided. By unpacking the events that must occur in order to provide value, we also identify the factors needed to compute the expected value that would be provided by a real diagnosis and recovery system. We then discuss the expected value we would estimate that such a system would have had for the Mars Exploration Rover mission. This has allowed us to identify the specific assumptions that made our expectations for MBD in this domain incorrect. [ABSTRACT FROM AUTHOR]

Many communication standards are available to set up consumer home networks. An intelligent combination of wired and wireless communication technologies allows exploiting many technology specific advantages while compensating disadvantages. Such a convergent digital home network infrastructure increases robustness, coverage range and availability of applications and services. In this paper, we discuss the general concept of such home networks. We present the Inter-MAC convergence sublayer as a very first approach to this concept. With the help of a typical scenario we demonstrate its feasibility. The recently initiated standardization activity IEEE P1905.1 is introduced. A global standard for convergent digital home networks can be the basis for a user-friendly network of consumer electronic devices in the home. [ABSTRACT FROM AUTHOR]