Author
Giorgio Rizzoni
Other affiliations: Ohio State University, University of Michigan
Bio: Giorgio Rizzoni is an academic researcher from Center for Automotive Research. The author has contributed to research in topics: Electric vehicle & Energy management. The author has an hindex of 61, co-authored 444 publications receiving 15245 citations. Previous affiliations of Giorgio Rizzoni include Ohio State University & University of Michigan.
Papers published on a yearly basis
Papers
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TL;DR: A new control strategy called Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) is presented, adding to the ECMS framework an on-the-fly algorithm for the estimation of the equivalence factor according to the driving conditions.
729 citations
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TL;DR: This paper presents three different energy management approaches for the control of a parallel hybrid electric sport-utility-vehicle that do not require a priori knowledge of the driving cycle and shows that the A-ECMS strategy is the best performing strategy.
Abstract: Hybrid electric vehicles (HEVs) improvements in fuel economy and emissions strongly depend on the energy management strategy. The parallel HEV control problem involves the determination of the time profiles of the power flows from the engine and the electric motor. This is also referred to as the power split between the conventional and the electric sources. The objective of HEV control is in fact to find out the sequence of optimal power splits at each instant of time that minimizes the fuel consumption over a given driving schedule. Big obstacles to the control design are the model complexity and the necessity of "a priori" knowledge of torque and velocity profiles. This paper presents three different energy management approaches for the control of a parallel hybrid electric sport-utility-vehicle that do not require a priori knowledge of the driving cycle. The considered approaches are: a rule-based control, an adaptive equivalent fuel consumption minimization strategy (A-ECMS), and the Hinfin control. Results, compared with the optimal solution given by the dynamic programming, show that the A-ECMS strategy is the best performing strategy
569 citations
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TL;DR: In this article, the authors present a formalization of the energy management problem in hybrid electric vehicles and a comparison of three known methods for solving the resulting optimization problem: dynamic programming, Pontryagin's minimum principle (PMP), and equivalent consumption minimization strategy (ECMS).
Abstract: This paper presents a formalization of the energy management problem in hybrid electric vehicles and a comparison of three known methods for solving the resulting optimization problem. Dynamic programming (DP), Pontryagin’s minimum principle (PMP), and equivalent consumption minimization strategy (ECMS) are described and analyzed, showing formally their substantial equivalence. Simulation results are also provided to demonstrate the application of the strategies. The theoretical background for each strategy is described in detail using the same formal framework. Of the three strategies, ECMS is the only implementable in real time; the equivalence with PMP and DP justifies its use as an optimal strategy and allows to tune it more effectively. DOI: 10.1115/1.4003267
480 citations
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10 Jun 2009TL;DR: An analytical derivation of the Equivalent Consumption Minimization Strategy (ECMS) for energy management of hybrid electric vehicles (HEVs) is presented, based on Pontryagin's minimum principle, valid for any powertrain architecture.
Abstract: An analytical derivation of the Equivalent Consumption Minimization Strategy (ECMS) for energy management of hybrid electric vehicles (HEVs) is presented, based on Pontryagin's minimum principle. The derivation is obtained using a generic formulation of the energy management problem in HEVs and is valid for any powertrain architecture. Simulation results obtained for a series HEV are also provided.
405 citations
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12 Dec 2005TL;DR: In this paper, a new control strategy called Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) is presented, which periodically refresh the control parameter according to the current road load, so that the battery State of Charge (SOC) is maintained within the boundaries and the fuel consumption is minimized.
Abstract: Hybrid Electric Vehicles (HEV) improvements in fuel economy and emissions strongly depend on the energy management strategy. In this paper a new control strategy called Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) is presented. This real-time energy management for HEV is obtained adding to the ECMS framework an on-the-fly algorithm for the estimation of the equivalence factor according to the driving conditions. The main idea is to periodically refresh the control parameter according to the current road load, so that the battery State of Charge (SOC) is maintained within the boundaries and the fuel consumption is minimized. The results obtained with A-ECMS show that the fuel economy that can be achieved is only slightly sub-optimal and the operations are charge-sustaining.
404 citations
Cited by
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TL;DR: This paper attempts to summarise and review the recent research and developments in diagnostics and prognostics of mechanical systems implementing CBM with emphasis on models, algorithms and technologies for data processing and maintenance decision-making.
3,848 citations
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27 Sep 2011TL;DR: Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research.
Abstract: There is an increasing demand for dynamic systems to become safer and more reliable This requirement extends beyond the normally accepted safety-critical systems such as nuclear reactors and aircraft, where safety is of paramount importance, to systems such as autonomous vehicles and process control systems where the system availability is vital It is clear that fault diagnosis is becoming an important subject in modern control theory and practice Robust Model-Based Fault Diagnosis for Dynamic Systems presents the subject of model-based fault diagnosis in a unified framework It contains many important topics and methods; however, total coverage and completeness is not the primary concern The book focuses on fundamental issues such as basic definitions, residual generation methods and the importance of robustness in model-based fault diagnosis approaches In this book, fault diagnosis concepts and methods are illustrated by either simple academic examples or practical applications The first two chapters are of tutorial value and provide a starting point for newcomers to this field The rest of the book presents the state of the art in model-based fault diagnosis by discussing many important robust approaches and their applications This will certainly appeal to experts in this field Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research The book is useful for both researchers in academia and professional engineers in industry because both theory and applications are discussed Although this is a research monograph, it will be an important text for postgraduate research students world-wide The largest market, however, will be academics, libraries and practicing engineers and scientists throughout the world
3,826 citations
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TL;DR: A bibliographical review on reconfigurable fault-tolerant control systems (FTCS) is presented, with emphasis on the reconfiguring/restructurable controller design techniques.
2,455 citations
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TL;DR: In this paper, the authors present the current status and implementation of battery chargers, charging power levels, and infrastructure for plug-in electric vehicles and hybrid vehicles and classify them into off-board and on-board types with unidirectional or bidirectional power flow.
Abstract: This paper reviews the current status and implementation of battery chargers, charging power levels, and infrastructure for plug-in electric vehicles and hybrids. Charger systems are categorized into off-board and on-board types with unidirectional or bidirectional power flow. Unidirectional charging limits hardware requirements and simplifies interconnection issues. Bidirectional charging supports battery energy injection back to the grid. Typical on-board chargers restrict power because of weight, space, and cost constraints. They can be integrated with the electric drive to avoid these problems. The availability of charging infrastructure reduces on-board energy storage requirements and costs. On-board charger systems can be conductive or inductive. An off-board charger can be designed for high charging rates and is less constrained by size and weight. Level 1 (convenience), Level 2 (primary), and Level 3 (fast) power levels are discussed. Future aspects such as roadbed charging are presented. Various power level chargers and infrastructure configurations are presented, compared, and evaluated based on amount of power, charging time and location, cost, equipment, and other factors.
2,327 citations