Design and lumped parameter magnetic network model of hybrid excited consequent pole flux switching machine

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Basharat Ullah ◽  
Faisal Khan ◽  
Bakhtiar Khan ◽  
Muhammad Yousuf
Keyword(s):  
Electric Vehicle ◽  
Network Model ◽  
Hybrid Electric Vehicle ◽  
Computational Time ◽  
Flux Linkage ◽  
Content Type ◽  
Lumped Parameter ◽  
Consequent Pole ◽  
Electromagnetic Performance ◽  
Magnetic Network

Purpose The purpose of this paper is to analyze electromagnetic performance and develop an analytical approach to find the suitable coil combination and no-load flux linkage of the proposed hybrid excited consequent pole flux switching machine (HECPFSM) while minimizing the drive storage and computational time which is the main problem in finite element analysis (FEA) tools. Design/methodology/approach First, a new HECPFSM based on conventional consequent pole flux switching permanent machine (FSPM) is proposed, and lumped parameter magnetic network model (LPMNM) is developed for the initial analysis like coil combination and no-load flux linkage. In LPMNM, all the parts of one-third machine are modeled which helps in reduction of drive storage, computational complexity and computational time without affecting the accuracy. Second, self and mutual inductance are calculated in the stator, and dq-axis inductance is calculated using park transformation in the rotor of the proposed machine. Furthermore, on-load performance analysis, like average torque, torque density and efficiency, is done by FEA. Findings The developed LPMNM is validated by FEA via JMAG v. 19.1. The results obtained show good agreement with an accuracy of 96.89%. Practical implications The proposed HECPFSM is developed for high-speed brushless AC applications like electric vehicle (EV)/hybrid electric vehicle (HEV). Originality/value The proposed HECPFSM offers better flux regulation capability with enhanced electromagnetic performance as compared to conventional consequent pole FSPM. Moreover, the developed LPMNM reduces drive storage and computational time by modeling one-third of the machine.

Lumped parameter magnetic equivalent circuit model for design of segmented PM consequent pole flux switching machine

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wasiq Ullah ◽  
Faisal Khan ◽  
Muhammad Umair
Keyword(s):  
Computational Complexity ◽  
Equivalent Circuit ◽  
Electric Machines ◽  
Frame Of Reference ◽  
Computational Time ◽  
Content Type ◽  
Lumped Parameter ◽  
Park Transformation ◽  
Consequent Pole ◽  
Electromagnetic Performance

Purpose The purpose of this paper is to investigate an alternative simplified analytical approach for the design of electric machines. Numerical-based finite element method (FEM) is a powerful tool for accurate modelling and electromagnetic performance analysis of electric machines. However, computational complexity, magnetic saturation, complex stator structure and time consumption compel researchers to adopt alternate analytical model for initial design of electric machine especially flux switching machines (FSMs). Design/methodology/approach In this paper, simplified lumped parameter magnetic equivalent circuit (LPMEC) model is presented for newly developed segmented PM consequent pole flux switching machine (SPMCPFSM). LPMEC model accounts influence of all machine parts for quarter of machine which helps to reduce computational complexity, computational time and drive storage without affecting overall accuracy. Furthermore, inductance calculation is performed in the rotor and stator frame of reference for accurate estimation of the self-inductance, mutual inductance and dq-axis inductance profile using park transformation. Findings The developed LPMEC model is validated with corresponding FEA using JMAG Commercial FEA Package v. 18.1 which shows good agreement with accuracy of ∼98.23%, and park transformation precisely estimates the inductance profile in rotor and stator frame of reference. Practical implications The model is developed for high-speed brushless AC applications. Originality/value The proposed SPMCPFSM enhance electromagnetic performance owing to partitioned PMs configuration which make it different than conventional designs. Moreover, the developed LPMEC model reduces computational time by solving quarter of machine.

Analytical methodologies for design of segmented permanent magnet consequent pole flux switching machine: a comparative analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wasiq Ullah ◽  
Faisal Khan ◽  
Muhammad Umair ◽  
Bakhtiar Khan
Keyword(s):  
Permanent Magnet ◽  
High Speed ◽  
Computational Cost ◽  
Domain Model ◽  
Design Stage ◽  
Computational Time ◽  
Magnetic Flux Density ◽  
Content Type ◽  
Consequent Pole ◽  
Electromagnetic Performance

Purpose This paper aims to reviewed analytical methodologies, i.e. lumped parameter magnetic equivalent circuit (LPMEC), magnetic co-energy (MCE), Laplace equations (LE), Maxwell stress tensor (MST) method and sub-domain modelling for design of segmented PM(SPM) consequent pole flux switching machine (SPMCPFSM). Electric machines, especially flux switching machines (FSMs), are accurately modeled using numerical-based finite element analysis (FEA) tools; however, despite of expensive hardware setup, repeated iterative process, complex stator design and permanent magnet (PM) non-linear behavior increases computational time and complexity. Design/methodology/approach This paper reviews various alternate analytical methodologies for electromagnetic performance calculation. In above-mentioned analytical methodologies, no-load phase flux linkage is performed using LPMEC, magnetic co-energy for cogging torque, LE for magnetic flux density (MFD) components, i.e. radial and tangential and MST for instantaneous torque. Sub-domain model solves electromagnetic performance, i.e. MFD and torque behaviour. Findings The reviewed analytical methodologies are validated with globally accepted FEA using JMAG Commercial FEA Package v. 18.1 which shows good agreement with accuracy. In comparison of analytical methodologies, analysis reveals that sub-domain model not only get rid of multiples techniques for validation purpose but also provide better results by accounting influence of all machine parts which helps to reduce computational complexity, computational time and drive storage with overall accuracy of ∼99%. Furthermore, authors are confident to recommend sub-domain model for initial design stage of SPMCPFSM when higher accuracy and low computational cost are primal requirements. Practical implications The model is developed for high-speed brushless AC applications. Originality/value The SPMCPFSM enhances electromagnetic performance owing to segmented PMs configuration which makes it different than conventional designs. Moreover, developed analytical methodologies for SPMCPFSM reduce computational time compared with that of FEA.

Can green taxation trigger plug-in hybrid electric vehicle acquisition?

2019 ◽  
Vol 14 (2) ◽  
pp. 168-186
Author(s):  
Victor Barros ◽  
Hugo Pádua
Keyword(s):  
Electric Vehicle ◽  
Financial Incentives ◽  
Structural Equation ◽  
Hybrid Electric Vehicle ◽  
Large Scale ◽  
Tax Reform ◽  
Financial Incentive ◽  
Content Type ◽  
Green Tax Reform ◽  
Hybrid Electric

Purpose The purpose of this paper is to analyse to what extent financial incentives under the green tax reform introduced in Portugal in 2014 drive behaviours of acquiring a plug-in hybrid electric vehicle (PHEV). Design/methodology/approach The existent literature identifies a number of factors that influence the interest for PHEV acquisition, including access to financial incentives. However, empirical evidence is not clear as to which factors are more relevant. The authors extend an existent theoretical model of five factors by including ten factors. On this basis, the study carries out a survey and develops a structural equation model to investigate what drives the interest to acquire a PHEV. Findings Financial incentives are superior to other factors in explaining the interest in acquiring a PHEV. Education, lower income levels, living in larger cities and driving smaller vehicles shape the interest on these vehicles differently. Financial incentives were found to closely offset the difference in price between conventional vehicles and plug-in hybrids. Social implications This study finds that public policies can be powerful in shaping consumers’ behaviour, although the amount of the financial incentive is key to triggering a large-scale effect. Originality/value The survey in this study allows an in-depth and ex ante analysis of the interest in acquiring PHEV under a green tax reform, taking into account other dimensions and socio-economic variables not accounted for in existent studies.

Hybrid Electric Vehicle Energy Management With Battery Thermal Considerations Using Multi-Rate Dynamic Programming

2013 ◽  
Author(s):  
Rajit Johri ◽  
Wei Liang ◽  
Ryan McGee
Keyword(s):  
Dynamic Programming ◽  
Electric Vehicle ◽  
Thermal Management ◽  
Hybrid Electric Vehicle ◽  
Computational Time ◽  
Bulk Temperature ◽  
Thermal Dynamics ◽  
Battery Thermal Management ◽  
Battery Capacity ◽  
Hybrid Electric

Battery capacity and battery thermal management control have a significant impact on the Hybrid Electric Vehicle (HEV) fuel economy. Additionally, battery temperature has a key influence on the battery health in an HEV. In the past, battery temperature and cooling capacity has not been included while performing optimization studies for power management or optimal battery sizing. This paper presents an application of Dynamic Programming (DP) to HEV optimization with battery thermal constraints. The optimization problem is formulated with 3 state variables, namely, the battery State Of Charge (SOC), the engine speed and the battery bulk temperature. This optimization is critical for determining appropriate battery size and battery thermal management design. The proposed problem has a major challenge in computation time due to the large state space. The paper describes a novel multi-rate DP algorithm to reduce the computational challenges associated with the particular class of large-scale problem where states evolve at very different rates. In HEV applications, the battery thermal dynamics is orders of magnitude slower than powertrain dynamics. The proposed DP algorithm provides a novel way of tackling this problem with multiple time rates for DP with each time rate associated with the fast and slow states separately. Additionally, the paper gives possible numerical techniques to reduce the DP computational time and the time reduction for each technique is shown.

scholarly journals Lumped Parameter Model and Electromagnetic Performance Analysis of a Single-Sided Variable Flux Permanent Magnet Linear Machine

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5494
Author(s):  
Basharat Ullah ◽  
Faisal Khan ◽  
Muhammad Qasim ◽  
Bakhtiar Khan ◽  
Ahmad H. Milyani ◽  
...  
Keyword(s):  
Permanent Magnet ◽  
Thrust Force ◽  
Lumped Parameter Model ◽  
Computational Time ◽  
Design Parameters ◽  
3D Analysis ◽  
Flux Linkage ◽  
Lumped Parameter ◽  
Variable Flux ◽  
Linear Machine

A new Single-sided Variable Flux Permanent Magnet Linear Machine with flux bridge in mover core is proposed in this paper. The flux bridge prevents the leakage flux from the mover and converts it into flux linkage, which greatly influences the performance of the machine. First, a lumped parameter model is used to find the suitable coil combination and no-load flux linkage of the proposed machine, which greatly reduces the computational time and drive storage. Secondly, the proposed machine replaces the expensive rare earth permanent magnets with ferrite magnets and provides improved flux controlling capability under variable excitation currents. Multivariable geometric optimization is utilized to optimize the leading design parameters like split ratio, stator pole width, width and height of permanent magnet, flux bridge width, the width of mover’s tooth, and stator slot depth at constant electric and magnetic loading. The optimized design increases the flux linkage by 44.11%, average thrust force by 35%, thrust force density by 35.02%, minimizes ripples in thrust force by 23%, and detent force by 87.5%. Furthermore, the results obtained by 2D analysis are verified by 3D analysis. Thermal analysis is done to set the operating limit of the proposed machine.

Analytical prediction of electromagnetic performance of dual-stator consequent-pole PM machines based on subdomain model accounting for tooth-tips

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Minchen Zhu ◽  
Lijian Wu ◽  
Dong Wang ◽  
Youtong Fang ◽  
Ping Tan
Keyword(s):  
Vector Potential ◽  
Analytical Prediction ◽  
Electromagnetic Torque ◽  
Induced Voltage ◽  
Fe Method ◽  
Content Type ◽  
Design And Optimization ◽  
Consequent Pole ◽  
Computational Resources ◽  
Electromagnetic Performance

Purpose The purpose of this paper is to analytically predict the on-load field distribution and electromagnetic performance (induced voltage, electromagnetic torque, winding inductances and unbalanced magnetic force) of dual-stator consequent-pole permanent magnet (DSCPPM) machines using subdomain model accounting for tooth-tip effect. The finite element (FE) results are presented to validate the accuracy of this subdomain model. Design/methodology/approach During the preliminary design and optimization of DSCPPM machines, FE method requires numerous computational resources and can be especially time-consuming. Thus, a subdomain model considering the tooth-tip effect is presented in this paper. The whole field domain is divided into four different types of sub-regions, where the analytical solutions of vector potential in each sub-region can be rapidly calculated. The proposed subdomain model can accurately predict the on-load flux density distributions and electromagnetic performance of DSCPPM machines, which is verified by FE method. Findings The radial and tangential components of flux densities in each sub-region of DSCPPM machine can be obtained according to the vector potential distribution, which is calculated based on the boundary and interface conditions using variable separation approach. The tooth-tip effect is investigated as well. Moreover, the phase-induced voltage, winding inductances, electromagnetic torque and X-axis/Y-axis components of unbalanced magnetic forces are calculated and compared by FE analysis, where excellent agreements are consistently exhibited. Originality/value The on-load field distributions and electromagnetic performance of DSCPPM machines are analytically investigated using subdomain method, which can be beneficial in the process of initial design and optimization for such DSCPPM machines.

Using the Pareto Set Pursuing Multiobjective Optimization Approach for Hybridization of a Plug-In Hybrid Electric Vehicle

2012 ◽  
Vol 134 (9) ◽  
Author(s):  
Shashi K. Shahi ◽  
G. Gary Wang ◽  
Liqiang An ◽  
Eric Bibeau ◽  
Zhila Pirmoradi
Keyword(s):  
Multiobjective Optimization ◽  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Operating Cost ◽  
Pareto Set ◽  
Computational Time ◽  
Design Parameters ◽  
Optimization Approach ◽  
Hybrid Electric

A plug-in hybrid electric vehicle (PHEV) can improve fuel economy and emission reduction significantly compared to hybrid electric vehicles and conventional internal combustion engine (ICE) vehicles. Currently there lacks an efficient and effective approach to identify the optimal combination of the battery pack size, electric motor, and engine for PHEVs in the presence of multiple design objectives such as fuel economy, operating cost, and emission. This work proposes a design approach for optimal PHEV hybridization. Through integrating the Pareto set pursuing (PSP) multiobjective optimization algorithm and powertrain system analysis toolkit (PSAT) simulator on a Toyota Prius PHEV platform, 4480 possible combinations of design parameters (20 batteries, 14 motors, and 16 engines) were explored for PHEV20 and PHEV40 powertrain configurations. The proposed approach yielded the optimal solution in a small fraction of computational time, as compared to an exhaustive search. This confirms the efficiency and applicability of PSP to problems with discrete variables. In the design context we have found that battery, motor, and engine collectively define the optimal hybridization scheme, which also varies with the drive cycle and all electric range (AER). The proposed method and software platform could be applied to optimize other powertrain designs.

scholarly journals A Consequent-Pole Magnetic-Geared Machine With Axially Embedded Permanent Magnets for Hybrid Electric Vehicle

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 14905-14917
Author(s):  
Shuangchun Xie ◽  
Hao Chen ◽  
Yuefei Zuo ◽  
Fawen Shen ◽  
Boon Siew Han ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Permanent Magnets ◽  
Hybrid Electric ◽  
Consequent Pole
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