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Special Issue "Power Management for Hybrids and Vehicle Drivetrains"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (1 May 2016)

Special Issue Editor

Guest Editor
Prof. Dr. Dirk Söffker

University of Duisburg-Essen, Chair of Dynamics and Control, Germany
Website | E-Mail
Interests: Modeling, diagnosis, and control of elastic mechanical structures; Advanced control: robust observers and robust control; Diagnosis and prognosis of technical systems; Cognitive technical systems: Automata and assistance

Special Issue Information

Dear Colleagues,

The hybridization of vehicle drive trains helps to overcome several conflicting requirements in the field of individual mobility. Overall fuel efficiency, exhaust behavior, drivability aspects, as well as design conflicts of the primary energy source will be strongly effected, introducing further energy storages between the primary source (ICE, FC, etc.) and the unknown highly dynamic power requirements realizing vehicle motion. Beside the characteristic properties of the hard components (motor, generator, fuel cell, storages, etc.), the soft components of drive trains, to control the energy flow in all directions based on measured, estimated, or assumed variables, are of importance. The focus of this Special Issue should be only on the soft components here denoted as power management. Power management includes controls, look-up-tables, adaption and learning strategies, sensor fusion, estimation and filtering approaches, optimization techniques, and is designed and applied to various drive train topologies and constellations. Common scientific tasks should be addressed in the Special Issue, addressing mechanical and electrical engineering aspects, as well as information science-oriented approaches.

To perfect the Special Issue “Power Management for Hybrids and Vehicle Drivetrains”, contributions should be clearly focused on the addressed research areas. Contributions should not be focused on hardware sizing aspects, pure numerical simulations studies, electronic circuits and related realizations, application reports, battery charging strategies, and should not only repeat known results (from previous works or the work of others). Prospective authors should provide original work with significant and novel contributions, providing new facts, ideas, insights, and results.

Prof. Dr. Dirk Söffker
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Power management strategies for hybrid vehicles
  • Power management strategies for vehicle drivetrains including motor management
  • Optimization of power management (online or offline), combined approaches
  • Optimization of architectures, algorithms, parameters
  • Optimization strategies related to power management design conflicts (fuel efficiency, drivability, aging, exhaust emission characteristics, etc.)
  • Aspects of integration of sources and storages with complex dynamical behavior on different scales
  • Consideration of individual driver/driving behavior
  • Drive cycles vs. real driving
  • Theory and practice/validation aspects of power management strategies
  • Adaptive, iterative, or learning behavior of power management considering variable conditions
  • Relations between standards, rules, or further requirements and realization of power management

Published Papers (5 papers)

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Research

Open AccessArticle Drivability-Related Discrete-Time Model Predictive Control of Mode Transition in Pre-Transmission Parallel Hybrid Powertrains
Energies 2016, 9(9), 740; doi:10.3390/en9090740
Received: 4 May 2016 / Revised: 5 September 2016 / Accepted: 6 September 2016 / Published: 13 September 2016
Cited by 1 | PDF Full-text (8014 KB) | HTML Full-text | XML Full-text
Abstract
During the mode transition from the pure electric propulsion mode to the hybrid propulsion mode, clutch-based pre-transmission parallel hybrid electric vehicles are subject to drivability issues. These issues originate from the fact that in the clutch-based pre-transmission parallel hybrid powertrain (CPPHP) configuration, the
[...] Read more.
During the mode transition from the pure electric propulsion mode to the hybrid propulsion mode, clutch-based pre-transmission parallel hybrid electric vehicles are subject to drivability issues. These issues originate from the fact that in the clutch-based pre-transmission parallel hybrid powertrain (CPPHP) configuration, the clutch connects the engine and the motor. Without a carefully designed mode transition control that coordinates the engine torque, clutch torque and motor torque, torque sluggishness and surges occur during the mode transition, and residual torque oscillation occurs after the mode transition. In this paper, a discrete-time model predictive control (DMPC)-based controller is proposed to address these drivability-related issues. Modeling improvements and novel drivability-related indices and constraints are all taken into consideration in the design of the discrete-time model predictive controller. Furthermore, by using discrete-time Laguerre functions and introducing the equilibrium state and the ranking of constraints, an explicit solution of the discrete-time model predictive controller is obtained. The calculation results demonstrate that the proposed controller can ensure a smooth and rapidly decaying torque difference during the mode transition, alleviating the residual torque oscillation after the mode transition and guaranteeing that the mode transition is completed within an acceptable duration. Full article
(This article belongs to the Special Issue Power Management for Hybrids and Vehicle Drivetrains)
Figures

Figure 1

Open AccessArticle Hybrid Modulation of Bidirectional Three-Phase Dual-Active-Bridge DC Converters for Electric Vehicles
Energies 2016, 9(7), 492; doi:10.3390/en9070492
Received: 9 March 2016 / Revised: 17 May 2016 / Accepted: 23 June 2016 / Published: 27 June 2016
Cited by 1 | PDF Full-text (7407 KB) | HTML Full-text | XML Full-text
Abstract
Bidirectional power converters for electric vehicles (EVs) have received much attention recently, due to either grid-supporting requirements or emergent power supplies. This paper proposes a hybrid modulation of the three-phase dual-active bridge (3ΦDAB) converter for EV charging systems. The designed hybrid modulation allows
[...] Read more.
Bidirectional power converters for electric vehicles (EVs) have received much attention recently, due to either grid-supporting requirements or emergent power supplies. This paper proposes a hybrid modulation of the three-phase dual-active bridge (3ΦDAB) converter for EV charging systems. The designed hybrid modulation allows the converter to switch its modulation between phase-shifted and trapezoidal modes to increase the conversion efficiency, even under light-load conditions. The mode transition is realized in a real-time manner according to the charging or discharging current. The operation principle of the converter is analyzed in different modes and thus design considerations of the modulation are derived. A lab-scaled prototype circuit with a 48V/20Ah LiFePO4 battery is established to validate the feasibility and effectiveness. Full article
(This article belongs to the Special Issue Power Management for Hybrids and Vehicle Drivetrains)
Figures

Open AccessArticle Online Power Management with Embedded Offline-Optimized Parameters for a Three-Source Hybrid Powertrain with an Experimental Emulation Application
Energies 2016, 9(6), 439; doi:10.3390/en9060439
Received: 29 February 2016 / Revised: 25 May 2016 / Accepted: 27 May 2016 / Published: 7 June 2016
Cited by 1 | PDF Full-text (22983 KB) | HTML Full-text | XML Full-text
Abstract
Real-time power management in the presence of one or more reversible energy storage systems is a current issue with hybrid electric vehicles (HEVs). To evaluate the potentials of rule-based power management, optimization with respect to two conflicting objectives, fuel consumption and state of
[...] Read more.
Real-time power management in the presence of one or more reversible energy storage systems is a current issue with hybrid electric vehicles (HEVs). To evaluate the potentials of rule-based power management, optimization with respect to two conflicting objectives, fuel consumption and state of charge (SoC) deviation, is considered in this contribution. A modular structure of power management with decoupled offline and online parts is presented. The online part incorporates look-up tables (LUTs) with parameters from the offline optimization part. This permits an inclusion of more LUTs corresponding to different drive patterns. The goal of this contribution is to combine the real-time applicability of rule-based power management and the multi-objective optimization property of genetic algorithms in a single control strategy. Component aging problems are addressed by suitable design. The influence of sizing is investigated. Finally, an experimental setup consisting of components capable of realizing the dynamics of real powertrain components is realized and introduced. A verification/plausibility assessment of modeled dynamics based on the literature is considered. This newly-introduced concept represents a class of power management, which is easy to implement, can tackle different objectives in real time, and adapt itself to unknown driver demands. Full article
(This article belongs to the Special Issue Power Management for Hybrids and Vehicle Drivetrains)
Open AccessArticle Development of Near Optimal Rule-Based Control for Plug-In Hybrid Electric Vehicles Taking into Account Drivetrain Component Losses
Energies 2016, 9(6), 420; doi:10.3390/en9060420
Received: 7 April 2016 / Revised: 4 May 2016 / Accepted: 19 May 2016 / Published: 31 May 2016
Cited by 3 | PDF Full-text (4609 KB) | HTML Full-text | XML Full-text
Abstract
A near-optimal rule-based mode control (RBC) strategy was proposed for a target plug-in hybrid electric vehicle (PHEV) taking into account the drivetrain losses. Individual loss models were developed for drivetrain components including the gears, planetary gear (PG), bearings, and oil pump, based on
[...] Read more.
A near-optimal rule-based mode control (RBC) strategy was proposed for a target plug-in hybrid electric vehicle (PHEV) taking into account the drivetrain losses. Individual loss models were developed for drivetrain components including the gears, planetary gear (PG), bearings, and oil pump, based on experimental data and mathematical governing equations. Also, a loss model for the power electronic system was constructed, including loss from the motor-generator while rotating in the unloaded state. To evaluate the effect of the drivetrain losses on the operating mode control strategy, backward simulations were performed using dynamic programming (DP). DP selects the operating mode, which provides the highest efficiency for given driving conditions. It was found that the operating mode selection changes when drivetrain losses are included, depending on driving conditions. An operating mode schedule was developed with respect to the wheel power and vehicle speed, and based on the operating mode schedule, a RBC was obtained, which can be implemented in an on-line application. To evaluate the performance of the RBC, a forward simulator was constructed for the target PHEV. The simulation results show near-optimal performance of the RBC compared with dynamic-programming-based mode control in terms of the mode operation time and fuel economy. The RBC developed with drivetrain losses taken into account showed a 4%–5% improvement of the fuel economy over a similar RBC, which neglected the drivetrain losses. Full article
(This article belongs to the Special Issue Power Management for Hybrids and Vehicle Drivetrains)
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Open AccessArticle Robust Longitudinal Speed Control of Hybrid Electric Vehicles with a Two-Degree-of-Freedom Fuzzy Logic Controller
Energies 2016, 9(4), 290; doi:10.3390/en9040290
Received: 6 January 2016 / Revised: 30 March 2016 / Accepted: 7 April 2016 / Published: 16 April 2016
Cited by 1 | PDF Full-text (4413 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a new robust two-degree-of-freedom (DoF) design method for controlling the nonlinear longitudinal speed problem of hybrid electric vehicles (HEVs). First, the uncertain parameters of the HEV model are described by fuzzy α-cut representation, in which the interval uncertainty and
[...] Read more.
This paper proposes a new robust two-degree-of-freedom (DoF) design method for controlling the nonlinear longitudinal speed problem of hybrid electric vehicles (HEVs). First, the uncertain parameters of the HEV model are described by fuzzy α-cut representation, in which the interval uncertainty and the possibility can be simultaneously indicated by the fuzzy membership function. For the fuzzy parametric uncertain system, the maximum uncertainty interval can be translated into the weighting matrix Q of the linear quadratic tracking problem to guarantee that the designed feedback controller is robust. Second, the fuzzy forward compensator is incorporated with a robust feedback controller to enhance the system tracking response. The simulation results demonstrate that the proposed controller has higher tracking performance compared to the single-DoF self-tuning fuzzy logic controller or conventional optimal H controller. Full article
(This article belongs to the Special Issue Power Management for Hybrids and Vehicle Drivetrains)

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