The Experts below are selected from a list of 40020 Experts worldwide ranked by ideXlab platform

Ilya Kolmanovsky - One of the best experts on this subject based on the ideXlab platform.

  • game theory controller for hybrid electric vehicles
    IEEE Transactions on Control Systems and Technology, 2014
    Co-Authors: Clement Dextreit, Ilya Kolmanovsky
    Abstract:

    This paper describes the development and experimental implementation of an energy management controller for hybrid electric vehicles (HEVs) based on the application of game theory (GT). This controller is constructed as a feedback Stackelberg equilibrium in the noncooperative game between the driver and the powertrain with the cost penalizing fuel consumption, NOx emissions, battery state of charge deviation, and vehicle operating conditions deviation. This control policy is drive-cycle and time independent. A description of the controller implementation with ancillary strategy elements is given. Experimental results from tests in a parallel HEV prototype vehicle are presented and compared with the existing baseline controller in terms of fuel consumption and NOx emissions. The HEV powertrain configuration is advanced and includes a high-speed diesel engine, two electric motors, and automated converterless transmission. Over the New European Driving Cycle (NEDC), the GT controller, with minimal calibration effort, demonstrates better performance than the existing baseline controller that is calibrated from the Deterministic Dynamic programing solution over NEDC. We also demonstrate that the GT controller substantially outperforms the baseline controller over other real-world-focused driving cycles while providing good drivability.

  • ultracapacitor assisted powertrains modeling control sizing and the impact on fuel economy
    IEEE Transactions on Control Systems and Technology, 2011
    Co-Authors: D Rotenberg, Ardalan Vahidi, Ilya Kolmanovsky
    Abstract:

    This paper considers modeling and energy management control problems for an automotive powertrain augmented with an ultracapacitor and an induction motor. The ultracapacitor-supplied motor assists the engine during periods of high power demand. The ultracapacitor may be recharged via regeneration during braking and by the engine during periods of low power demand. A reduced-order model and a detailed simulation model of the powertrain are created for control design and evaluation of fuel economy, respectively. A heuristic rule-based controller is used for testing the impact of different component combinations on fuel economy. After a suitable combination of engine, motor, and ultracapacitor sizes has been determined, a model predictive control strategy is created for power management which achieves better fuel economy than the rule-based approach. Various component sizing and control strategies tested consistently indicate a potential for 5% to 15% improvement in fuel economy in city driving with the proposed mild hybrid powertrain. This order of improvement to fuel economy was confirmed by Deterministic Dynamic programming which finds the best possible fuel economy.

  • ultracapacitor assisted powertrains modeling control sizing and the impact on fuel economy
    American Control Conference, 2008
    Co-Authors: D Rotenberg, Ardalan Vahidi, Ilya Kolmanovsky
    Abstract:

    A mild parallel hybrid powertrain is considered in which an electric motor and an ultracapacitor-based energy source assist the combustion engine during periods of high power demand. The ultracapacitor may be recharged by the engine during periods of low demand, and through regenerative braking. A rule-based control strategy is defined, which determines the power split between the engine and motor. Standard city-cycle simulations on a full-order model of the powertrain illustrate an improvement in fuel economy enabled by the ultracapacitor-based mild hybrid configuration and this control strategy. The Deterministic Dynamic programming is also applied to the reduced-order model of the powertrain to assess fuel economy potential of the hybrid system under pointwise-in-time and terminal constraints on the state of charge and motor power limits.

R L Geiger - One of the best experts on this subject based on the ideXlab platform.

  • testing high resolution adcs with low resolution accuracy Deterministic Dynamic element matched dacs
    IEEE Transactions on Instrumentation and Measurement, 2007
    Co-Authors: Hanjun Jiang, B Olleta, Degang Chen, R L Geiger
    Abstract:

    This paper presents a Deterministic Dynamic element matching (DDEM) approach, which is applied to low-precision digital-to-analog converters (DACs) to generate uniformly spaced voltage samples for analog-to-digital converter (ADC) testing. Theoretical analysis is provided to show the test performance using this DDEM DAC. Both simulation results and experimental results from a fabricated DDEM DAC are presented to verify the performance. The ADC testing performance, by using an 8-bit DDEM DAC (linearity less than 5 bits without DDEM), is comparable to the best results reported in the literature using on-chip linear ramp generators. The DDEM technique offers great potential for use in both production test and built-in-self-test (BIST) environments.

  • a Deterministic Dynamic element matching approach for testing high resolution adcs with low accuracy excitations
    IEEE Transactions on Instrumentation and Measurement, 2006
    Co-Authors: B Olleta, Degang Chen, Hanjun Jiang, R L Geiger
    Abstract:

    Dynamic element matching (DEM) is capable of providing good average linearity performance in matching critical circuits in the presence of major component mismatch, but the approach has received minimal industrial adoption outside of Sigma-Delta structures because of challenges associated with implementation of a required randomizer and because of the time-local nonstationarity. This paper presents a DEM approach to analog-to-digital converter (ADC) testing in which low-precision DEM digital-to-analog converters (DACs) are used to generate stimulus signals for ADCs under test. It is shown that in a testing environment, this approach provides very high precision test results, and time-local nonstationarity is of no concern. In addition to traditional random DEM techniques, a Deterministic DEM (DDEM) strategy that eliminates the need for a randomizer is introduced. The performance of the DDEM method is established mathematically and validated with detailed simulation results. Furthermore, the DDEM method requires far fewer samples to achieve the same level of average linearity than the random DEM approach. It is demonstrated that both the random DEM and DDEM methods can be used to accurately test ADCs with linearity that far exceeds that of the DAC used as a signal generator. This technique of using imprecise excitations and DEM to test much more accurate ADCs offers potential for use in both production test and built-in self-test environments where high linearity test sources are difficult to implement

  • testing high resolution adcs with low resolution accuracy Deterministic Dynamic element matched dacs
    International Test Conference, 2004
    Co-Authors: Hanjun Jiang, B Olleta, Degang Chen, R L Geiger
    Abstract:

    This work presents a Deterministic Dynamic element matching (DDEM) approach which is applied to low precision DACs to generate stimulus signals for ADC testing. Both simulation results and experimental results from a fabricated DDEM DAC are presented to verify the performance. The ADC testing performance of an 8-bit DDEM DAC (linearity less than 5 bits without DDEM) is comparable to or better than the best results reported in the literature using on-chip linear ramp generators. The DDEM technique offers great potential for use in both production test and built-in-self-test(BIST) environments.

  • parameter optimization of Deterministic Dynamic element matching dacs for accurate and cost effective adc testing
    International Symposium on Circuits and Systems, 2004
    Co-Authors: Hanjun Jiang, B Olleta, Degang Chen, R L Geiger
    Abstract:

    Deterministic Dynamic element matching (DDEM) is applied to low accuracy DACs for high resolution ADC test. The testing accuracy is impressive while the test cost is relatively low. This work tries to further optimize the DDEM parameters based on improving the test accuracy and reducing the test hardware and computation cost. The optimization is accomplished by theoretical analysis and numerical simulation. Some typical parameter values are suggested by this work.

  • a Deterministic Dynamic element matching approach to adc testing
    International Symposium on Circuits and Systems, 2003
    Co-Authors: B Olleta, L Juffer, Degang Chen, R L Geiger
    Abstract:

    A Deterministic Dynamic element matching (DEM) approach to ADC testing is introduced and compared with a common random DEM method. With both approaches, a highly non-ideal DAC is used to generate an excitation for a DUT that has linearity that far exceeds that of the test stimulus. Simulation results show that both methods can be used for testing of ADCs but with a substantial reduction in the number of samples required for the Deterministic DEM method. This technique of using an imprecise excitation to test an accurate ADC offers potential for use in both production test and BIST environments.

Peter Bro Miltersen - One of the best experts on this subject based on the ideXlab platform.

  • error correcting codes perfect hashing circuits and Deterministic Dynamic dictionaries
    Symposium on Discrete Algorithms, 1998
    Co-Authors: Peter Bro Miltersen
    Abstract:

    We consider dictionaries of size n over the finite universe U = {0, 1} and introduce a new technique for their implementation: error correcting codes. The use of such codes makes it possible to replace the use of strong forms of hashing, such as universal hashing, with much weaker forms, such as clustering. We use our approach to construct, for any > 0, a Deterministic solution to the Dynamic dictionary problem using linear space, with worst case time O(n ) for insertions and deletions, and worst case time O(1) for lookups. This is the first Deterministic solution to the Dynamic dictionary problem with linear space, constant query time, and non-trivial update time. In particular, we get a solution to the static dictionary problem with O(n) space, worst case query time O(1), and Deterministic initialization time O(n1+ ). The best previous Deterministic initialization time for such dictionaries, due to Andersson, is O(n2+ ). The model of computation for these bounds is a unit cost ∗Supported by the ESPRIT Long Term Research Programme of the EU under project number 20244 (ALCOM-IT). †Basic Research in Computer Science, Centre of the Danish National Research Foundation

  • error correcting codes perfect hashing circuits and Deterministic Dynamic dictionaries
    BRICS Report Series, 1997
    Co-Authors: Peter Bro Miltersen
    Abstract:

    We consider dictionaries of size n over the finite universe U ={0, 1}^w and introduce a new technique for their implementation: error correcting codes. The use of such codes makes it possible to replace the use of strong forms of hashing, such as universal hashing, with much weaker forms, such as clustering. We use our approach to construct, for any epsilon > 0, a Deterministic solution to the Dynamic dictionary problem using linear space, with worst case time O(n) for insertions and deletions, and worst case time O(1) for lookups. This is the first Deterministic solution to the Dynamic dictionary problem with linear space, constant query time, and non-trivial update time. In particular, we get a solution to the static dictionary problem with O(n) space, worst case query time O(1), and Deterministic initialization time O(n^(1+epsilon)). The best previous Deterministic initialization time for such dictionaries, due to Andersson, is O(n^(2+epsilon)). The model of computation for these bounds is a unit cost RAM with word size w (i.e. matching the universe), and a standard instruction set. The constants in the big-O's are independent upon w. The solutions are weakly non-uniform in w, i.e. the code of the algorithm contains word sized constants, depending on w, which must be computed at compile-time, rather than at run-time, for the stated run-time bounds to hold. An ingredient of our proofs, which may be interesting in its own right, is the following observation: A good error correcting code for a bit vector fitting into a word can be computed in O(1) time on a RAM with unit cost multiplication. As another application of our technique in a different model of computation, we give a new construction of perfect hashing circuits, improving a construction by Goldreich and Wigderson. In particular, we show that for any subset S of {0;1}w of size n, there is a Boolean circuit C of size O(w log w) with w inputs and 2 log n outputs so that the function defined by C is 1-1 on S. The best previous bound on the size of such a circuit was O(w log w log log w).

Albert Sola Vilalta - One of the best experts on this subject based on the ideXlab platform.

  • control of two energy storage units with market impact lagrangian approach and horizons
    IEEE International Conference on Probabilistic Methods Applied to Power Systems, 2020
    Co-Authors: Miguel F Anjos, James Cruise, Albert Sola Vilalta
    Abstract:

    Energy storage and demand-side response will play an increasingly important role in the future electricity system. We extend previous results on a single energy storage unit to the management of two energy storage units cooperating for the purpose of price arbitrage. We consider a Deterministic Dynamic programming model for the cooperative problem, which accounts for market impact. We develop the Lagrangian theory and present a new algorithm to identify pairs of strategies. While we are not able to prove that the algorithm provides optimal strategies, we give strong numerical evidence in favour of it. Furthermore, the Lagrangian approach makes it possible to identify decision and forecast horizons, the latter being a time beyond which it is not necessary to look in order to determine the present optimal action. In practice, this allows for real-time reoptimization, with both horizons being of the order of days.

  • control of two energy storage units with market impact lagrangian approach and horizons
    arXiv: Optimization and Control, 2020
    Co-Authors: Miguel F Anjos, James Cruise, Albert Sola Vilalta
    Abstract:

    Energy storage and demand-side response will play an increasingly important role in the future electricity system. We extend previous results on a single storage unit to the management of two energy storage units cooperating for the purpose of price arbitrage. We consider a Deterministic Dynamic programming model for the cooperative problem, which accounts for market impact. We develop the Lagrangian theory and present a new algorithm to identify pairs of strategies. While we are not able to prove that the algorithm provides optimal strategies, we give strong numerical evidence in favour of it. Furthermore, the Lagrangian approach makes it possible to identify decision and forecast horizons, the latter being a time beyond which it is not necessary to look in order to determine the present optimal action. In practice, this allows for real-time reoptimization, with both horizons being of the order of days.

  • control of two energy storage units with market impact lagrangian approach and horizons
    arXiv: Optimization and Control, 2020
    Co-Authors: Miguel F Anjos, James Cruise, Albert Sola Vilalta
    Abstract:

    Energy storage and demand-side response will play an increasingly important role in the future electricity system. We extend previous results on a single energy storage unit to the management of two energy storage units cooperating for the purpose of price arbitrage. We consider a Deterministic Dynamic programming model for the cooperative problem, which accounts for market impact. We develop the Lagrangian theory and present a new algorithm to identify pairs of strategies. While we are not able to prove that the algorithm provides optimal strategies, we give strong numerical evidence in favour of it. Furthermore, the Lagrangian approach makes it possible to identify decision and forecast horizons, the latter being a time beyond which it is not necessary to look in order to determine the present optimal action. In practice, this allows for real-time reoptimization, with both horizons being of the order of days. Index Terms-control, two storage units, arbitrage, pricemaker, market impact, energy, Lagrangian.

B Olleta - One of the best experts on this subject based on the ideXlab platform.

  • testing high resolution adcs with low resolution accuracy Deterministic Dynamic element matched dacs
    IEEE Transactions on Instrumentation and Measurement, 2007
    Co-Authors: Hanjun Jiang, B Olleta, Degang Chen, R L Geiger
    Abstract:

    This paper presents a Deterministic Dynamic element matching (DDEM) approach, which is applied to low-precision digital-to-analog converters (DACs) to generate uniformly spaced voltage samples for analog-to-digital converter (ADC) testing. Theoretical analysis is provided to show the test performance using this DDEM DAC. Both simulation results and experimental results from a fabricated DDEM DAC are presented to verify the performance. The ADC testing performance, by using an 8-bit DDEM DAC (linearity less than 5 bits without DDEM), is comparable to the best results reported in the literature using on-chip linear ramp generators. The DDEM technique offers great potential for use in both production test and built-in-self-test (BIST) environments.

  • a Deterministic Dynamic element matching approach for testing high resolution adcs with low accuracy excitations
    IEEE Transactions on Instrumentation and Measurement, 2006
    Co-Authors: B Olleta, Degang Chen, Hanjun Jiang, R L Geiger
    Abstract:

    Dynamic element matching (DEM) is capable of providing good average linearity performance in matching critical circuits in the presence of major component mismatch, but the approach has received minimal industrial adoption outside of Sigma-Delta structures because of challenges associated with implementation of a required randomizer and because of the time-local nonstationarity. This paper presents a DEM approach to analog-to-digital converter (ADC) testing in which low-precision DEM digital-to-analog converters (DACs) are used to generate stimulus signals for ADCs under test. It is shown that in a testing environment, this approach provides very high precision test results, and time-local nonstationarity is of no concern. In addition to traditional random DEM techniques, a Deterministic DEM (DDEM) strategy that eliminates the need for a randomizer is introduced. The performance of the DDEM method is established mathematically and validated with detailed simulation results. Furthermore, the DDEM method requires far fewer samples to achieve the same level of average linearity than the random DEM approach. It is demonstrated that both the random DEM and DDEM methods can be used to accurately test ADCs with linearity that far exceeds that of the DAC used as a signal generator. This technique of using imprecise excitations and DEM to test much more accurate ADCs offers potential for use in both production test and built-in self-test environments where high linearity test sources are difficult to implement

  • testing high resolution adcs with low resolution accuracy Deterministic Dynamic element matched dacs
    International Test Conference, 2004
    Co-Authors: Hanjun Jiang, B Olleta, Degang Chen, R L Geiger
    Abstract:

    This work presents a Deterministic Dynamic element matching (DDEM) approach which is applied to low precision DACs to generate stimulus signals for ADC testing. Both simulation results and experimental results from a fabricated DDEM DAC are presented to verify the performance. The ADC testing performance of an 8-bit DDEM DAC (linearity less than 5 bits without DDEM) is comparable to or better than the best results reported in the literature using on-chip linear ramp generators. The DDEM technique offers great potential for use in both production test and built-in-self-test(BIST) environments.

  • parameter optimization of Deterministic Dynamic element matching dacs for accurate and cost effective adc testing
    International Symposium on Circuits and Systems, 2004
    Co-Authors: Hanjun Jiang, B Olleta, Degang Chen, R L Geiger
    Abstract:

    Deterministic Dynamic element matching (DDEM) is applied to low accuracy DACs for high resolution ADC test. The testing accuracy is impressive while the test cost is relatively low. This work tries to further optimize the DDEM parameters based on improving the test accuracy and reducing the test hardware and computation cost. The optimization is accomplished by theoretical analysis and numerical simulation. Some typical parameter values are suggested by this work.

  • a Deterministic Dynamic element matching approach to adc testing
    International Symposium on Circuits and Systems, 2003
    Co-Authors: B Olleta, L Juffer, Degang Chen, R L Geiger
    Abstract:

    A Deterministic Dynamic element matching (DEM) approach to ADC testing is introduced and compared with a common random DEM method. With both approaches, a highly non-ideal DAC is used to generate an excitation for a DUT that has linearity that far exceeds that of the test stimulus. Simulation results show that both methods can be used for testing of ADCs but with a substantial reduction in the number of samples required for the Deterministic DEM method. This technique of using an imprecise excitation to test an accurate ADC offers potential for use in both production test and BIST environments.