Energies

Research

7881 KiB

Open AccessArticle

A Supervisory Control Algorithm of Hybrid Electric Vehicle Based on Adaptive Equivalent Consumption Minimization Strategy with Fuzzy PI

by Fengqi Zhang, Haiou Liu, Yuhui Hu and Junqiang Xi

Energies 2016, 9(11), 919; https://doi.org/10.3390/en9110919 - 8 Nov 2016

Cited by 36 | Viewed by 6377

Abstract

This paper presents a new energy management system based on equivalent consumption minimization strategy (ECMS) for hybrid electric vehicles. The aim is to enhance fuel economy and impose state of charge (SoC) charge-sustainability. First, the relationship between the equivalent factor (EF) [...] Read more.

This paper presents a new energy management system based on equivalent consumption minimization strategy (ECMS) for hybrid electric vehicles. The aim is to enhance fuel economy and impose state of charge (SoC) charge-sustainability. First, the relationship between the equivalent factor (EF) of ECMS and the co-state of pontryagin’s minimum principle (PMP) is derived. Second, a new method of implementing the adaptation law using fuzzy proportional plus integral (PI) controller is developed to adjust EF for ECMS in real-time. This adaptation law is more robust than one with constant EF due to the variation of EF as well as driving cycle. Finally, simulations for two driving cycles using ECMS are conducted as opposed to the commonly used rule-based (RB) control strategy, indicating that the proposed adaptation law can provide a promising blend in terms of fuel economy and charge-sustainability. The results confirm that ECMS with Fuzzy PI adaptation law is more robust than ECMS with constant EF as well as PI adaptation law and it achieves significant improvements compared with RB in terms of fuel economy, which is enhanced by 4.44% and 14.7% for china city bus cycle and economic commission of Europe (ECE) cycle, respectively. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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2248 KiB

Open AccessArticle

A Rest Time-Based Prognostic Framework for State of Health Estimation of Lithium-Ion Batteries with Regeneration Phenomena

by Taichun Qin, Shengkui Zeng, Jianbin Guo and Zakwan Skaf

Energies 2016, 9(11), 896; https://doi.org/10.3390/en9110896 - 1 Nov 2016

Cited by 46 | Viewed by 6061

Abstract

State of health (SOH) prognostics is significant for safe and reliable usage of lithium-ion batteries. To accurately predict regeneration phenomena and improve long-term prediction performance of battery SOH, this paper proposes a rest time-based prognostic framework (RTPF) in which the beginning time interval [...] Read more.

State of health (SOH) prognostics is significant for safe and reliable usage of lithium-ion batteries. To accurately predict regeneration phenomena and improve long-term prediction performance of battery SOH, this paper proposes a rest time-based prognostic framework (RTPF) in which the beginning time interval of two adjacent cycles is adopted to reflect the rest time. In this framework, SOH values of regeneration cycles, the number of cycles in regeneration regions and global degradation trends are extracted from raw SOH time series and predicted respectively, and then the three sets of prediction results are integrated to calculate the final overall SOH prediction values. Regeneration phenomena can be found by support vector machine and hyperplane shift (SVM-HS) model by detecting long beginning time intervals. Gaussian process (GP) model is utilized to predict the global degradation trend, and nonlinear models are utilized to predict the regeneration amplitude and the cycle number of each regeneration region. The proposed framework is validated through experimental data from the degradation tests of lithium-ion batteries. The results demonstrate that both the global degradation trend and the regeneration phenomena of the testing batteries can be well predicted. Moreover, compared with the published methods, more accurate SOH prediction results can be obtained under this framework. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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7147 KiB

Open AccessArticle

Optimal Isolation Control of Three-Port Active Converters as a Combined Charger for Electric Vehicles

by Zhixiang Ling, Hui Wang, Kun Yan and Jinhao Gan

Energies 2016, 9(9), 715; https://doi.org/10.3390/en9090715 - 6 Sep 2016

Cited by 15 | Viewed by 5655

Abstract

The three-port converter has three H-bridge ports that can interface with three different energy sources and offers the advantages of flexible power transmission, galvanic isolation ability and high power density. The three-port full-bridge converter can be used in electric vehicles as a combined [...] Read more.

The three-port converter has three H-bridge ports that can interface with three different energy sources and offers the advantages of flexible power transmission, galvanic isolation ability and high power density. The three-port full-bridge converter can be used in electric vehicles as a combined charger that consists of a battery charger and a DC-DC converter. Power transfer occurs between two ports while the third port is isolated, i.e., the average power is zero. The purpose of this paper is to apply an optimal phase shift strategy in isolation control and provide a detailed comparison between traditional phase shift control and optimal phase shift control under the proposed isolation control scheme, including comparison of the zero-voltage-switching range and the root mean square current for the two methods. Based on this analysis, the optimal parameters are selected. The results of simulations and experiments are given to verify the advantages of dual-phase-shift control in isolation control. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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5780 KiB

Open AccessArticle

A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles

by Jun Yang, Jiejun Chen, Lei Chen, Feng Wang, Peiyuan Xie and Cilin Zeng

Energies 2016, 9(9), 670; https://doi.org/10.3390/en9090670 - 24 Aug 2016

Cited by 12 | Viewed by 5255

Abstract

With the popularization of electric vehicles (EVs), the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban [...] Read more.

With the popularization of electric vehicles (EVs), the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban zone is divided into four regions, a regional time-of-use (RTOU) electricity price model is proposed to guide EVs when and where to charge considering spatial and temporal characteristics. In light of the elastic coefficient, the user response to the RTOU electricity price is analyzed, and also a bilayer optimization charging strategy including regional-layer and node-layer models is suggested to schedule the EVs. On the one hand, the regional layer model is designed to coordinate the EVs located in different time and space. On the other hand, the node layer model is built to schedule the EVs to charge in certain nodes. According to the simulations of an IEEE 33-bus distribution network, the performance of the proposed optimal charging strategy is verified. The results demonstrate that the proposed bilayer optimization strategy can effectively decrease the charging cost of users, mitigate the peak-valley load difference and the network loss. Besides, the RTOU electricity price shows better performance than the time-of-use (TOU) electricity price. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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5016 KiB

Open AccessEditor’s ChoiceArticle

New Electro-Thermal Battery Pack Model of an Electric Vehicle

by Muhammed Alhanouti, Martin Gießler, Thomas Blank and Frank Gauterin

Energies 2016, 9(7), 563; https://doi.org/10.3390/en9070563 - 20 Jul 2016

Cited by 27 | Viewed by 14284

Abstract

Since the evolution of the electric and hybrid vehicle, the analysis of batteries’ characteristics and influence on driving range has become essential. This fact advocates the necessity of accurate simulation modeling for batteries. Different models for the Li-ion battery cell are reviewed in [...] Read more.

Since the evolution of the electric and hybrid vehicle, the analysis of batteries’ characteristics and influence on driving range has become essential. This fact advocates the necessity of accurate simulation modeling for batteries. Different models for the Li-ion battery cell are reviewed in this paper and a group of the highly dynamic models is selected for comparison. A new open circuit voltage (OCV) model is proposed. The new model can simulate the OCV curves of lithium iron magnesium phosphate (LiFeMgPO₄) battery type at different temperatures. It also considers both charging and discharging cases. The most remarkable features from different models, in addition to the proposed OCV model, are integrated in a single hybrid electrical model. A lumped thermal model is implemented to simulate the temperature development in the battery cell. The synthesized electro-thermal battery cell model is extended to model a battery pack of an actual electric vehicle. Experimental tests on the battery, as well as drive tests on the vehicle are performed. The proposed model demonstrates a higher modeling accuracy, for the battery pack voltage, than the constituent models under extreme maneuver drive tests. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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5850 KiB

Open AccessArticle

Risk Assessment of Distribution Networks Considering the Charging-Discharging Behaviors of Electric Vehicles

by Jun Yang, Wanmeng Hao, Lei Chen, Jiejun Chen, Jing Jin and Feng Wang

Energies 2016, 9(7), 560; https://doi.org/10.3390/en9070560 - 19 Jul 2016

Cited by 17 | Viewed by 6186

Abstract

Electric vehicles (EVs) have received wide attention due to their higher energy efficiency and lower emissions. However, the random charging and discharging behaviors of substantial numbers of EVs may lead to safety risk problems in a distribution network. Reasonable price incentives can guide [...] Read more.

Electric vehicles (EVs) have received wide attention due to their higher energy efficiency and lower emissions. However, the random charging and discharging behaviors of substantial numbers of EVs may lead to safety risk problems in a distribution network. Reasonable price incentives can guide EVs through orderly charging and discharging, and further provide a feasible solution to reduce the operational risk of the distribution network. Considering three typical electricity prices, EV charging/discharging load models are built. Then, a Probabilistic Load Flow (PLF) method using cumulants and Gram-Charlier series is proposed to obtain the power flow of the distribution network including massive numbers of EVs. In terms of the risk indexes of node voltage and line flow, the operational risk of the distribution network can be estimated in detail. From the simulations of an IEEE-33 bus system and an IEEE 69-bus system, the demonstrated results show that reasonable charging and discharging prices are conducive to reducing the peak-valley difference, and consequently the risks of the distribution network can be decreased to a certain extent. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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3200 KiB

Open AccessArticle

Novel Parametric Circuit Modeling for Li-Ion Batteries

by Ximing Cheng, Liguang Yao, Yinjiao Xing and Michael Pecht

Energies 2016, 9(7), 539; https://doi.org/10.3390/en9070539 - 14 Jul 2016

Cited by 13 | Viewed by 6193

Abstract

Because of their simplicity and dynamic response, current pulse series are often used to extract parameters for equivalent electrical circuit modeling of Li-ion batteries. These models are then applied for performance simulation, state estimation, and thermal analysis in electric vehicles. However, these methods [...] Read more.

Because of their simplicity and dynamic response, current pulse series are often used to extract parameters for equivalent electrical circuit modeling of Li-ion batteries. These models are then applied for performance simulation, state estimation, and thermal analysis in electric vehicles. However, these methods have two problems: The assumption of linear dependence of the matrix columns and negative parameters estimated from discrete-time equations and least-squares methods. In this paper, continuous-time equations are exploited to construct a linearly independent data matrix and parameterize the circuit model by the combination of non-negative least squares and genetic algorithm, which constrains the model parameters to be positive. Trigonometric functions are then developed to fit the parameter curves. The developed model parameterization methodology was applied and assessed by a standard driving cycle. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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4385 KiB

Open AccessArticle

Electric Vehicle to Power Grid Integration Using Three-Phase Three-Level AC/DC Converter and PI-Fuzzy Controller

by Khairy Sayed and Hossam A. Gabbar

Energies 2016, 9(7), 532; https://doi.org/10.3390/en9070532 - 11 Jul 2016

Cited by 60 | Viewed by 19310

Abstract

This paper presents the control and simulation of an electric vehicle (EV) charging station using a three-level converter on the grid-side as well as on the EV-side. The charging station control schemes with three-level AC/DC power conversion and a bidirectional DC/DC charging regulator [...] Read more.

This paper presents the control and simulation of an electric vehicle (EV) charging station using a three-level converter on the grid-side as well as on the EV-side. The charging station control schemes with three-level AC/DC power conversion and a bidirectional DC/DC charging regulator are described. The integration of EVs to the power grid provides an improvement of the grid reliability and stability. EVs are considered an asset to the smart grid to optimize effective performance economically and environmentally under various operation conditions, and more significantly to sustain the resiliency of the grid in the case of emergency conditions and disturbance events. The three-level grid side converter (GSC) can participate in the reactive power support or grid voltage control at the grid interfacing point or the common coupling point (PCC). A fuzzy logic proportional integral (FL-PI) controller is proposed to control the GSC converter. The controllers used are verified and tested by simulation to evaluate their performance using MATLAB/SIMULINK. The comparison of a PI-controller and a PI-Fuzzy controller for the EV charging station shows the effectiveness of the proposed FL-PI controller over conventional PI controller for same circuit operating conditions. A good performance for PI-Fuzzy in terms of settling time and peak overshoot can observed from the simulation results. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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5436 KiB

Open AccessArticle

Initial Energy Logistics Cost Analysis for Stationary, Quasi-Dynamic, and Dynamic Wireless Charging Public Transportation Systems

by Young Jae Jang, Seungmin Jeong and Min Seok Lee

Energies 2016, 9(7), 483; https://doi.org/10.3390/en9070483 - 23 Jun 2016

Cited by 104 | Viewed by 10881

Abstract

This paper presents an initial investment cost analysis of public transportation systems operating with wireless charging electric vehicles (EVs). There are three different types of wireless charging systems, namely, stationary wireless charging (SWC), in which charging happens only when the vehicle is [...] Read more.

This paper presents an initial investment cost analysis of public transportation systems operating with wireless charging electric vehicles (EVs). There are three different types of wireless charging systems, namely, stationary wireless charging (SWC), in which charging happens only when the vehicle is parked or idle, quasi-dynamic wireless charging (QWC), in which power is transferred when a vehicle is moving slowly or in stop-and-go mode, and dynamic wireless charging (DWC), in which power can be supplied even when the vehicle is in motion. This analysis compares the initial investment costs for these three types of charging systems for a wireless charging-based public transportation system. In particular, this analysis is focused on the energy logistics cost in transportation, which is defined as the cost of transferring and storing the energy needed to operate the transportation system. Performing this initial investment analysis is complicated, because it involves considerable tradeoffs between the costs of batteries in the EV fleet and different kinds of battery-charging infrastructure. Mathematical optimization models for each type of EV and infrastructure system are used to analyze the initial costs. The optimization methods evaluate the minimum initial investment needed to deploy the public transportation system for each type of EV charging solution. To deal with the variable cost estimates for batteries and infrastructure equipment in the current market, a cost-sensitivity analysis is performed. The goal of this analysis is to identify the market cost conditions that are most favorable for each type of wireless charging solution. Furthermore, the cost analysis quantitatively verifies the qualitative comparison of the three different wireless charging types conducted in the previous research. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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4033 KiB

Open AccessArticle

Online Diagnosis for the Capacity Fade Fault of a Parallel-Connected Lithium Ion Battery Group

by Hua Zhang, Lei Pei, Jinlei Sun, Kai Song, Rengui Lu, Yongping Zhao, Chunbo Zhu and Tiansi Wang

Energies 2016, 9(5), 387; https://doi.org/10.3390/en9050387 - 20 May 2016

Cited by 29 | Viewed by 7138

Abstract

In a parallel-connected battery group (PCBG), capacity degradation is usually caused by the inconsistency between a faulty cell and other normal cells, and the inconsistency occurs due to two potential causes: an aging inconsistency fault or a loose contacting fault. In this paper, [...] Read more.

In a parallel-connected battery group (PCBG), capacity degradation is usually caused by the inconsistency between a faulty cell and other normal cells, and the inconsistency occurs due to two potential causes: an aging inconsistency fault or a loose contacting fault. In this paper, a novel method is proposed to perform online and real-time capacity fault diagnosis for PCBGs. Firstly, based on the analysis of parameter variation characteristics of a PCBG with different fault causes, it is found that PCBG resistance can be taken as an indicator for both seeking the faulty PCBG and distinguishing the fault causes. On one hand, the faulty PCBG can be identified by comparing the PCBG resistance among PCBGs; on the other hand, two fault causes can be distinguished by comparing the variance of the PCBG resistances. Furthermore, for online applications, a novel recursive-least-squares algorithm with restricted memory and constraint (RLSRMC), in which the constraint is added to eliminate the “imaginary number” phenomena of parameters, is developed and used in PCBG resistance identification. Lastly, fault simulation and validation results demonstrate that the proposed methods have good accuracy and reliability. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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3033 KiB

Open AccessArticle

A Study on Price-Based Charging Strategy for Electric Vehicles on Expressways

by Lixing Chen, Zhong Chen, Xueliang Huang and Long Jin

Energies 2016, 9(5), 385; https://doi.org/10.3390/en9050385 - 19 May 2016

Cited by 19 | Viewed by 5729

Abstract

With the large-scale adoption of electric vehicles (EVs) on expressways, the exploration of a guiding-based charging method to effectively adjust interactions between EVs and the fast charging stations (CSs) is urgently needed. This paper proposes a status-of-use (SOU) price-based charging strategy that can [...] Read more.

With the large-scale adoption of electric vehicles (EVs) on expressways, the exploration of a guiding-based charging method to effectively adjust interactions between EVs and the fast charging stations (CSs) is urgently needed. This paper proposes a status-of-use (SOU) price-based charging strategy that can motivate users to charge in advance. A queuing model for a CS cluster was established to verify the effectiveness of the strategy, and then a simulation of traveling and charging conditions of 12,000 pure EVs on the road network from 0:00 to 24:00 was performed according to the related data and using the Monte Carlo method, the Floyd-Warshall algorithm, and the queuing algorithm proposed in this paper. Compared to unordered charging (UC), SOU price-based charging can not only reduce the charging cost and waiting time for users, but also increase the utilization ratio of charging facilities in a CS cluster and thus lower their influence on the power grid and expressway traffic. SOU price-based charging can effectively adjust interactions between EVs and CSs. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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2536 KiB

Open AccessArticle

A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles

by Yinuo Huang, Chuangxin Guo, Yi Ding, Licheng Wang, Bingquan Zhu and Lizhong Xu

Energies 2016, 9(5), 370; https://doi.org/10.3390/en9050370 - 16 May 2016

Cited by 8 | Viewed by 4746

Abstract

Coordinated dispatch of plug-in electric vehicles (PEVs) with renewable energies has been proposed in recent years. However, it is difficult to achieve effective PEV dispatch with a win-win result, which not only optimizes power system operation, but also satisfies the requirements of PEV [...] Read more.

Coordinated dispatch of plug-in electric vehicles (PEVs) with renewable energies has been proposed in recent years. However, it is difficult to achieve effective PEV dispatch with a win-win result, which not only optimizes power system operation, but also satisfies the requirements of PEV owners. In this paper, a multi-period PEV dispatch framework, combining day-ahead dispatch with real-time dispatch, is proposed. On the one hand, the day-ahead dispatch is used to make full use of wind power and minimize the fluctuation of total power in the distribution system, and schedule the charging/discharging power of PEV stations for each period. On the other hand, the real-time dispatch arranges individual PEVs to meet the charging/discharging power demands of PEV stations given by the day-ahead dispatch. To reduce the dimensions of the resulting large-scale, non-convex problem, PEVs are clustered according to their travel information. An interval optimization model is introduced to obtain the problem solution of the day-ahead dispatch. For the real-time dispatch, a priority-ordering method is developed to satisfy the requirements of PEV owners with fast response. Numerical studies demonstrate the effectiveness of the presented framework. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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19740 KiB

Open AccessArticle

Lithium Ion Batteries—Development of Advanced Electrical Equivalent Circuit Models for Nickel Manganese Cobalt Lithium-Ion

by Alexandros Nikolian, Yousef Firouz, Rahul Gopalakrishnan, Jean-Marc Timmermans, Noshin Omar, Peter Van den Bossche and Joeri Van Mierlo

Energies 2016, 9(5), 360; https://doi.org/10.3390/en9050360 - 11 May 2016

Cited by 78 | Viewed by 11606

Abstract

In this paper, advanced equivalent circuit models (ECMs) were developed to model large format and high energy nickel manganese cobalt (NMC) lithium-ion 20 Ah battery cells. Different temperatures conditions, cell characterization test (Normal and Advanced Tests), ECM topologies (1st and 2nd Order Thévenin [...] Read more.

In this paper, advanced equivalent circuit models (ECMs) were developed to model large format and high energy nickel manganese cobalt (NMC) lithium-ion 20 Ah battery cells. Different temperatures conditions, cell characterization test (Normal and Advanced Tests), ECM topologies (1st and 2nd Order Thévenin model), state of charge (SoC) estimation techniques (Coulomb counting and extended Kalman filtering) and validation profiles (dynamic discharge pulse test (DDPT) and world harmonized light vehicle profiles) have been incorporated in the analysis. A concise state-of-the-art of different lithium-ion battery models existing in the academia and industry is presented providing information about model classification and information about electrical models. Moreover, an overview of the different steps and information needed to be able to create an ECM model is provided. A comparison between begin of life (BoL) and aged (95%, 90% state of health) ECM parameters (internal resistance (R_o), polarization resistance (R_p), activation resistance (R_p2) and time constants (τ) is presented. By comparing the BoL to the aged parameters an overview of the behavior of the parameters is introduced and provides the appropriate platform for future research in electrical modeling of battery cells covering the ageing aspect. Based on the BoL parameters 1st and 2nd order models were developed for a range of temperatures (15 °C, 25 °C, 35 °C, 45 °C). The highest impact to the accuracy of the model (validation results) is the temperature condition that the model was developed. The 1st and 2nd order Thévenin models and the change from normal to advanced characterization datasets, while they affect the accuracy of the model they mostly help in dealing with high and low SoC linearity problems. The 2nd order Thévenin model with advanced characterization parameters and extended Kalman filtering SoC estimation technique is the most efficient and dynamically correct ECM model developed. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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1196 KiB

Open AccessArticle

Vibration Durability Testing of Nickel Cobalt Aluminum Oxide (NCA) Lithium-Ion 18650 Battery Cells

by James Michael Hooper, James Marco, Gael Henri Chouchelamane, Christopher Lyness and James Taylor

Energies 2016, 9(4), 281; https://doi.org/10.3390/en9040281 - 12 Apr 2016

Cited by 28 | Viewed by 8743

Abstract

This paper outlines a study undertaken to determine if the electrical performance of Nickel Cobalt Aluminum Oxide (NCA) 3.1 Ah 18650 battery cells can be degraded by road induced vibration typical of an electric vehicle (EV) application. This study investigates if a particular [...] Read more.

This paper outlines a study undertaken to determine if the electrical performance of Nickel Cobalt Aluminum Oxide (NCA) 3.1 Ah 18650 battery cells can be degraded by road induced vibration typical of an electric vehicle (EV) application. This study investigates if a particular cell orientation within the battery assembly can result in different levels of cell degradation. The 18650 cells were evaluated in accordance with Society of Automotive Engineers (SAE) J2380 standard. This vibration test is synthesized to represent 100,000 miles of North American customer operation at the 90th percentile. This study identified that both the electrical performance and the mechanical properties of the NCA lithium-ion cells were relatively unaffected when exposed to vibration energy that is commensurate with a typical vehicle life. Minor changes observed in the cell’s electrical characteristics were deemed not to be statistically significant and more likely attributable to laboratory conditions during cell testing and storage. The same conclusion was found, irrespective of cell orientation during the test. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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2930 KiB

Open AccessArticle

Optimization of Shift Schedule for Hybrid Electric Vehicle with Automated Manual Transmission

by Wenchen Shen, Huilong Yu, Yuhui Hu and Junqiang Xi

Energies 2016, 9(3), 220; https://doi.org/10.3390/en9030220 - 19 Mar 2016

Cited by 28 | Viewed by 8179

Abstract

Currently, most hybrid electric vehicles (HEVs) equipped with automated mechanical transmission (AMT) are implemented with the conventional two-parameter gear shift schedule based on engineering experience. However, this approach cannot take full advantage of hybrid drives. In other words, the powertrain of an HEV [...] Read more.

Currently, most hybrid electric vehicles (HEVs) equipped with automated mechanical transmission (AMT) are implemented with the conventional two-parameter gear shift schedule based on engineering experience. However, this approach cannot take full advantage of hybrid drives. In other words, the powertrain of an HEV is not able to work at the best fuel-economy points during the whole driving profile. To solve this problem, an optimization method of gear shift schedule for HEVs is proposed based on Dynamic Programming (DP) and a corresponding solving algorithm is also put forward. A gear shift schedule that can be employed in real-vehicle is extracted from the obtained optimal gear shift points by DP approach and is optimized based on analysis of the engineering experience in a typical Chinese urban driving cycle. Compared with the conventional two-parameter gear shift schedule in both simulation and real vehicle experiments, the extracted gear shift schedule is proved to clearly improve the fuel economy of the HEV. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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9300 KiB

Open AccessArticle

A High-Gain Three-Port Power Converter with Fuel Cell, Battery Sources and Stacked Output for Hybrid Electric Vehicles and DC-Microgrids

by Ching-Ming Lai and Ming-Ji Yang

Energies 2016, 9(3), 180; https://doi.org/10.3390/en9030180 - 9 Mar 2016

Cited by 29 | Viewed by 8111

Abstract

This paper proposes a novel high-gain three-port power converter with fuel cell (FC), battery sources and stacked output for a hybrid electric vehicle (HEV) connected to a dc-microgrid. In the proposed power converter, the load power can be flexibly distributed between the input [...] Read more.

This paper proposes a novel high-gain three-port power converter with fuel cell (FC), battery sources and stacked output for a hybrid electric vehicle (HEV) connected to a dc-microgrid. In the proposed power converter, the load power can be flexibly distributed between the input sources. Moreover, the charging or discharging of the battery storage device can be controlled effectively using the FC source. The proposed converter has several outputs in series to achieve a high-voltage output, which makes it suitable for interfacing with the HEV and dc-microgrid. On the basis of the charging and discharging states of the battery storage device, two power operation modes are defined. The proposed power converter comprises only one boost inductor integrated with a flyback transformer; the boost and flyback circuit output terminals are stacked to increase the output voltage gain and reduce the voltage stress on the power devices. This paper presents the circuit configuration, operating principle, and steady-state analysis of the proposed converter, and experiments conducted on a laboratory prototype are presented to verify its effectiveness. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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2530 KiB

Open AccessArticle

Aggregator-Based Interactive Charging Management System for Electric Vehicle Charging

by Mingchao Xia, Qingying Lai, Yajiao Zhong, Canbing Li and Hsiao-Dong Chiang

Energies 2016, 9(3), 159; https://doi.org/10.3390/en9030159 - 4 Mar 2016

Cited by 35 | Viewed by 9059

Abstract

With the ongoing large-scale implementation of electric vehicles (EVs), the exploration of a more flexible approach to maintain fair interaction between EVs and the power grid is urgently required. This paper presents an aggregator-based interactive charging management scheme adopting interruptible load (IL) pricing, [...] Read more.

With the ongoing large-scale implementation of electric vehicles (EVs), the exploration of a more flexible approach to maintain fair interaction between EVs and the power grid is urgently required. This paper presents an aggregator-based interactive charging management scheme adopting interruptible load (IL) pricing, in which the EV aggregator will respond to the load control command of the grid in an EV interactive mode. Charging managements are carried out according to battery state-of-charge and the EV departure time in EV charging stations. A power-altering charging (PAC) control method is proposed to dispatch the EVs charging fairly in a station and guarantee EV owners’ preferences. The method does not require classical iterative procedures or heavy computations; furthermore, it is beneficial for EVs to depart earlier than expected for reasons beyond keeping homeostatic charging. The proposed scheme, which is tested to charge individual EVs well according to its preference, was implemented as part of an “EV Beijing” project. The proposed management scheme provides new insight into EV charging strategy and provides another choice to EV users. Full article

(This article belongs to the Special Issue Energy Storage Systems for Plug-in Electric Vehicles and Vehicle to Power Grid Integration)

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