Special Issue "Plug-in Hybrid Electric Vehicle (PHEV)"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy".

Deadline for manuscript submissions: 31 December 2018

Special Issue Editor

Guest Editor
Prof. Dr. Joeri Van Mierlo

Mobility, Logistics and Automotive Technology Research Centre (MOBI), Vrije Universiteit Brussel, Pleinlaan 2, Brussel 1050, Belgium
Website | E-Mail
Interests: Electric and Hybrid vehicles; Batteries; Power converters, Energy management; Vehicle simulations; Life cycle assessment (LCA); Total cost of ownership (TCO)

Special Issue Information

Dear Colleagues,

Climate change, urban air quality, and dependency on crude oil are important societal challenges. In the transportation sector, especially, clean and energy efficient technologies must be developed. Electric Vehicles (EVs) and Plug-in Hybrid Electric Electric Vehicles (PHEVs) have gained a growing interest in vehicle industry. Nowadays, the commercialization of EVs and PHEVs has been possible in different applications (i.e., light duty, medium duty, and heavy duty vehicles) thanks to the advances in energy-storage systems, power electronics converters (incl. DC/DC converters, DC/AC inverters and battery charging systems), electric machines, and energy efficient power flow control strategies.

This Special Issue is focused on the recent advances in electric vehicles and plug-in electric vehicles that address the new powertrain developments and go beyond the state-of-the-art (SOTA).

Topics of interest include novel propulsion systems, emerging power electronics and their control algorithms, emerging electric machines and control techniques, energy storage systems, including BMS, efficient energy management strategies for hybrid propulsion systems, vehicle-to-grid (V2G), vehicle-to-home (V2H), grid-to-vehicle (G2V) technologies and wireless power transfer systems (WPTs).

Prof. Dr. ir. Joeri Van  Mierlo
Guest Editor

Manuscript Submission Information

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Keywords

  • Plug-in Hybrid electric Vehicles
  • Power Electronics converters for energy efficient drives for electric vehicles
  • Energy management systems in plug-in hybrid vehicles
  • V2G, G2V and V2H
  • Charging infrastructure
  • Energy storage

Published Papers (8 papers)

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Research

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Open AccessArticle Experimental Evaluation and Prediction Algorithm Suggestion for Determining SOC of Lithium Polymer Battery in a Parallel Hybrid Electric Vehicle
Appl. Sci. 2018, 8(9), 1641; https://doi.org/10.3390/app8091641
Received: 3 September 2018 / Revised: 7 September 2018 / Accepted: 10 September 2018 / Published: 13 September 2018
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Abstract
The necessity of hybrid vehicles and electric vehicles is widely known for reasons such as fossil fuel depletion, climate change, emission norms mandated by regulations, and so on. Expansion of the hybrid vehicle market is a realistic way to respond to fuel efficiency
[...] Read more.
The necessity of hybrid vehicles and electric vehicles is widely known for reasons such as fossil fuel depletion, climate change, emission norms mandated by regulations, and so on. Expansion of the hybrid vehicle market is a realistic way to respond to fuel efficiency regulations. Hybrid electric vehicles are continuously challenged to meet cross-attribute performance while minimizing energy usage and component cost in a highly competitive automotive market. Current optimization strategy for a parallel hybrid requires much computational time and relies heavily on the drive cycle to accurately represent driving conditions in the future. With increasing application of the lithium-ion battery technology in the automotive industry, development processes and validation methods for the battery management system (BMS) have attracted attention. The purpose of this study is to propose an algorithm to analyze charging characteristics and improve accuracy for determining state of charge (SOC), the equivalent of a fuel gauge for the battery pack, during the regenerative braking period of a TMED type parallel hybrid electric vehicle. Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Open AccessArticle Optimized Multiport DC/DC Converter for Vehicle Drivetrains: Topology and Design Optimization
Appl. Sci. 2018, 8(8), 1351; https://doi.org/10.3390/app8081351
Received: 20 June 2018 / Revised: 7 August 2018 / Accepted: 9 August 2018 / Published: 11 August 2018
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Abstract
DC/DC Multiport Converters (MPC) are gaining interest in the hybrid electric drivetrains (i.e., vehicles or machines), where multiple sources are combined to enhance their capabilities and performances in terms of efficiency, integrated design and reliability. This hybridization will lead to more complexity and
[...] Read more.
DC/DC Multiport Converters (MPC) are gaining interest in the hybrid electric drivetrains (i.e., vehicles or machines), where multiple sources are combined to enhance their capabilities and performances in terms of efficiency, integrated design and reliability. This hybridization will lead to more complexity and high development/design time. Therefore, a proper design approach is needed to optimize the design of the MPC as well as its performance and to reduce development time. In this research article, a new design methodology based on a Multi-Objective Genetic Algorithm (MOGA) for non-isolated interleaved MPCs is developed to minimize the weight, losses and input current ripples that have a significant impact on the lifetime of the energy sources. The inductor parameters obtained from the optimization framework is verified by the Finite Element Method (FEM) COMSOL software, which shows that inductor weight of optimized design is lower than that of the conventional design. The comparison of input current ripples and losses distribution between optimized and conventional designs are also analyzed in detailed, which validates the perspective of the proposed optimization method, taking into account emerging technologies such as wide bandgap semiconductors (SiC, GaN). Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Open AccessFeature PaperArticle Battery Aging Prediction Using Input-Time-Delayed Based on an Adaptive Neuro-Fuzzy Inference System and a Group Method of Data Handling Techniques
Appl. Sci. 2018, 8(8), 1301; https://doi.org/10.3390/app8081301
Received: 3 July 2018 / Revised: 31 July 2018 / Accepted: 2 August 2018 / Published: 4 August 2018
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Abstract
In this article, two techniques that are congruous with the principle of control theory are utilized to estimate the state of health (SOH) of real-life plug-in hybrid electric vehicles (PHEVs) accurately, which is of vital importance to battery management systems. The relation between
[...] Read more.
In this article, two techniques that are congruous with the principle of control theory are utilized to estimate the state of health (SOH) of real-life plug-in hybrid electric vehicles (PHEVs) accurately, which is of vital importance to battery management systems. The relation between the battery terminal voltage curve properties and the battery state of health is modelled via an adaptive neuron-fuzzy inference system and a group method of data handling. The comparison of the results demonstrates the capability of the proposed techniques for accurate SOH estimation. Moreover, the estimated results are compared with the direct actual measured SOH indicators using standard tests. The results indicate that the adaptive neuron-fuzzy inference system with fifteen rules based on a SOH estimator has better performances over the other technique, with a 1.5% maximum error in comparison to the experimental data. Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Open AccessArticle Hybrid Battery/Lithium-Ion Capacitor Energy Storage System for a Pure Electric Bus for an Urban Transportation Application
Appl. Sci. 2018, 8(7), 1176; https://doi.org/10.3390/app8071176
Received: 30 May 2018 / Revised: 12 July 2018 / Accepted: 17 July 2018 / Published: 19 July 2018
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Abstract
Public transportation based on electric vehicles has attracted significant attention in recent years due to the lower overall emissions it generates. However, there are some barriers to further development and commercialization. Fewer charging facilities in comparison to gas stations, limited battery lifetime, and
[...] Read more.
Public transportation based on electric vehicles has attracted significant attention in recent years due to the lower overall emissions it generates. However, there are some barriers to further development and commercialization. Fewer charging facilities in comparison to gas stations, limited battery lifetime, and extra costs associated with its replacement present some barriers to achieve better acceptance. A practical solution to improve the battery lifetime and driving range is to eliminate the large-magnitude pulse current flow from and to the battery during acceleration and deceleration. Hybrid energy storage systems which combine high-power (HP) and high-energy (HE) storage units can be used for this purpose. Lithium-ion capacitors (LiC) can be used as a HP storage unit, which is similar to a supercapacitor cell but with a higher rate capability, a higher energy density, and better cyclability. In this design, the LiC can provide the excess power required while the battery fails to do so. Moreover, hybridization enables a downsizing of the overall energy storage system and decreases the total cost as a consequence of lifetime, performance, and efficiency improvement. The aim of this paper is to investigate the effectiveness of the hybrid energy storage system in protecting the battery from damage due to the high-power rates during charging and discharging. The procedure followed and presented in this paper demonstrates the good performance of the evaluated hybrid storage system to reduce the negative consequences of the power peaks associated with urban driving cycles and its ability to improve the lifespan by 16%. Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Open AccessArticle In-Life Range Modularity for Electric Vehicles: The Environmental Impact of a Range-Extender Trailer System
Appl. Sci. 2018, 8(7), 1016; https://doi.org/10.3390/app8071016
Received: 28 April 2018 / Revised: 11 June 2018 / Accepted: 17 June 2018 / Published: 21 June 2018
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Abstract
Purpose: In the light of decarbonizing the passenger car sector, several technologies are available today. In this paper, we distinguish plug-in hybrid electric vehicles (PHEV), electric vehicles (EV) with a modest battery capacity of 40 kWh, and long-range EVs with 90 kWh
[...] Read more.
Purpose: In the light of decarbonizing the passenger car sector, several technologies are available today. In this paper, we distinguish plug-in hybrid electric vehicles (PHEV), electric vehicles (EV) with a modest battery capacity of 40 kWh, and long-range EVs with 90 kWh installed. Given that the average motorist only rarely performs long-distance trips, both the PHEV and the 90 kWh EV are considered to be over-dimensioned for their purpose, although consumers tend to perceive the 40 kWh EV’s range as too limiting. Therefore, in-life range modularity by means of occasionally using a range-extender trailer for a 40 kWh EV is proposed, based on either a petrol generator as a short-term solution or a 50 kWh battery pack. Method: A life cycle assessment (LCA) is presented for comparing the different powertrains for their environmental impact, with the emphasis on local air quality and climate change. Therefore, the combination of a 40 kWh EV and the trailer options is benchmarked with a range of conventional cars and EVs, differentiated per battery capacity. Next, the local impact per technology is discussed on a well-to-wheel base for the specific situation in Belgium, with specific attention given to the contribution of non-exhaust emissions of PM due to brake, tyre, and road wear. Results: From a life cycle point of view, the trailer concepts outperform the 90 kWh EV for the discussed midpoint indicators as the latter is characterized by a high manufacturing impact and by a mass penalty resulting in higher contributions to non-exhaust PM formation. Compared to a petrol PHEV, both trailers are found to have higher contributions to diminished local air quality, given the relatively low use phase impact of petrol combustion. Concerning human toxicity, the impact is proportional to battery size, although the battery trailer performs better than the 90 kWh EV due to its occasional application rather than carrying along such high capacity all the time. For climate change, we see a clear advantage of both the petrol and the battery trailer, with reductions ranging from one-third to nearly sixty percent, respectively. Conclusion: Whereas electrified powertrains have the potential to add to better urban air quality, their life cycle impact cannot be neglected as battery manufacturing remains a substantial contributor to the EV’s overall impact. Therefore, in-life range modularity helps to reduce this burden by offering an extended range only when it is needed. This is relevant to bridge the years up until cleaner battery chemistries break through, while the energy production sector increases the implementation of renewables. Petrol generator trailers are no long-term solution but should be seen as an intermediate means until battery technology costs have further dropped to make it economically feasible to commercialize battery trailer range-extenders. Next, active regulation is required for non-exhaust PM emissions as they could dominate locally in the future if more renewables would be applied in the electricity production process. Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Open AccessArticle Power Sharing and Voltage Vector Distribution Model of a Dual Inverter Open-End Winding Motor Drive System for Electric Vehicles
Appl. Sci. 2018, 8(2), 254; https://doi.org/10.3390/app8020254
Received: 4 January 2018 / Revised: 1 February 2018 / Accepted: 5 February 2018 / Published: 8 February 2018
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Abstract
A drive system with an open-end winding permanent magnet synchronous motor (OW-PMSM) fed by a dual inverter and powered by two independent power sources is suitable for electric vehicles. By using an energy conversion device as primary power source and an energy storage
[...] Read more.
A drive system with an open-end winding permanent magnet synchronous motor (OW-PMSM) fed by a dual inverter and powered by two independent power sources is suitable for electric vehicles. By using an energy conversion device as primary power source and an energy storage element as secondary power source, this configuration can not only lower the DC-bus voltage and extend the driving range, but also handle the power sharing between two power sources without a DC/DC (direct current to direct current) converter. Based on a drive system model with voltage vector distribution, this paper proposes a desired power sharing calculation method and three different voltage vector distribution methods. By their selection strategy the optimal voltage vector distribution method can be selected according to the operating conditions. On the basis of the integral synthesizing of the desired voltage vector, the proposed voltage vector distribution method can reduce the inverter switching frequency while making the primary power source follow its desired output power. Simulation results confirm the validity of the proposed methods, which improve the primary power source’s energy efficiency by regulating its output power and lessen inverter switching loss by reducing the switching frequency. This system also provides an approach to the energy management function of electric vehicles. Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Open AccessArticle Comparisons of Energy Management Methods for a Parallel Plug-In Hybrid Electric Vehicle between the Convex Optimization and Dynamic Programming
Appl. Sci. 2018, 8(2), 218; https://doi.org/10.3390/app8020218
Received: 13 December 2017 / Revised: 26 January 2018 / Accepted: 28 January 2018 / Published: 31 January 2018
Cited by 2 | PDF Full-text (5211 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a comparison study of energy management methods for a parallel plug-in hybrid electric vehicle (PHEV). Based on detailed analysis of the vehicle driveline, quadratic convex functions are presented to describe the nonlinear relationship between engine fuel-rate and battery charging power
[...] Read more.
This paper proposes a comparison study of energy management methods for a parallel plug-in hybrid electric vehicle (PHEV). Based on detailed analysis of the vehicle driveline, quadratic convex functions are presented to describe the nonlinear relationship between engine fuel-rate and battery charging power at different vehicle speed and driveline power demand. The engine-on power threshold is estimated by the simulated annealing (SA) algorithm, and the battery power command is achieved by convex optimization with target of improving fuel economy, compared with the dynamic programming (DP) based method and the charging depleting–charging sustaining (CD/CS) method. In addition, the proposed control methods are discussed at different initial battery state of charge (SOC) values to extend the application. Simulation results validate that the proposed strategy based on convex optimization can save the fuel consumption and reduce the computation burden obviously. Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Review

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Open AccessReview Electricity Generation in LCA of Electric Vehicles: A Review
Appl. Sci. 2018, 8(8), 1384; https://doi.org/10.3390/app8081384
Received: 25 July 2018 / Revised: 10 August 2018 / Accepted: 13 August 2018 / Published: 16 August 2018
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Abstract
Life Cycle assessments (LCAs) on electric mobility are providing a plethora of diverging results. 44 articles, published from 2008 to 2018 have been investigated in this review, in order to find the extent and the reason behind this deviation. The first hurdle can
[...] Read more.
Life Cycle assessments (LCAs) on electric mobility are providing a plethora of diverging results. 44 articles, published from 2008 to 2018 have been investigated in this review, in order to find the extent and the reason behind this deviation. The first hurdle can be found in the goal definition, followed by the modelling choice, as both are generally incomplete and inconsistent. These gaps influence the choices made in the Life Cycle Inventory (LCI) stage, particularly in regards to the selection of the electricity mix. A statistical regression is made with results available in the literature. It emerges that, despite the wide-ranging scopes and the numerous variables present in the assessments, the electricity mix’s carbon intensity can explain 70% of the variability of the results. This encourages a shared framework to drive practitioners in the execution of the assessment and policy makers in the interpretation of the results. Full article
(This article belongs to the Special Issue Plug-in Hybrid Electric Vehicle (PHEV))
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Tentative Title: The Battery Life time impact in an electrified vehicle by reducing durations with high SOC levels

Authors: Torbjörn Thiringer and Evelina Wikner
Abstract: In this article, the impact of ageing when using various SOC levels for an electrified vehicle is investigated. An extensive test series is conducted on Li-ion cells based on NMC/LMO technique. Cycling has been conducted during a period of more than one year in 10 % SOC intervals, and the degradation as function of used SOC level is established. For cycling in SOC intervals lower than 30 % the degradation is found to be very moderate,6 % at 3000 Full Cycle Equivalents (FCE’s), compared to 20 % degradation for 3000 FCE with a SOC level of higher than 60 %. After determining the degrading trajectories as function of SOC level, an empirical battery ageing model is designed from the test cells and implemented in an electrified vehicle model running according to three drive cycles. By keeping the SOC low, whenever possible, the battery life-time can be increased substantially.

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