Optimisation-based control for electrified vehicles: challenges and opportunities

Sun, Jing

doi:10.1080/23307706.2015.1010634

Cited by 13 publications

(4 citation statements)

References 53 publications

(43 reference statements)

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“…EVs have existed for over 100 years [21], but have only become economically viable and popular in the last 10-20 years [22], making it an exciting and growing potential market for companies to capitalise on. The industry's movement towards the adoption of EVs was supposed to, in theory, lower the barriers to entry to the market due to having fewer moving parts within the car and increased ease of assembly [23].…”

Section: Ev Supply Chain Managementmentioning

confidence: 99%

A SWOT Analysis of the UK EV Battery Supply Chain

et al. 2020

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The aim of this research is to identify and explore the UK electric vehicle (EV) battery industry’s supply chain strengths, weaknesses, opportunities and threats (SWOT) by taking a leading UK EV battery company as an exploratory case study. Our research addresses the gap in knowledge surrounding the UK EV battery supply chain, as the current literature is limited whilst demands for EVs are surging. There are significant opportunities awaiting the EV battery industry, though it is crucial that companies are aware of the threats facing them. To address the gap, this research followed an exploratory qualitative research design using semi-structured interviews with experienced interviewees in the industry. By applying the SWOT analysis framework and the theory lens of Resource Based View (RBV), we suggest that the UK EV battery industry should diversify its supply base into multiple regions such as India, Africa, and the US, which would reduce the reliance on sourcing from China whilst maintaining good supplier relationships and continuous innovation.

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Section: Ev Supply Chain Managementmentioning

confidence: 99%

A SWOT Analysis of the UK EV Battery Supply Chain

et al. 2020

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“…naval weapons and high-power radar) (Dedes et al, 2012), brake energy recuperation and back-up power (Geertsma et al, 2017). In order to enhance these functions, an agile control scheme is necessary to decide working profiles of engine-generators and batteries in such a way that the fuel consumption and emissions of the engines are minimised while the machine performance is guaranteed (Sun, 2015).…”

Section: Distribution Busmentioning

confidence: 99%

Optimal Control and Real-Time Simulation of Hybrid Marine Power Plants

Dinh

Bui

Marco

et al. 2018

Proceedings of the International Naval Engineering Conference and Exhibition (INEC)

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With significantly increasing concerns about greenhouse effects and sustainable economy, the marine industry presents great potential for reducing its environmental impact. Recent developments in power electronics and hybridisation technologies create new opportunities for innovative marine power plants which utilize both traditional diesel generators and energy storage like batteries and/or supercapacitors as the power sources. However, power management of such complex systems in order to achieve the best efficiency becomes one of the major challenges. Acknowledging this importance, this research aims to develop an optimal control strategy (OCS) for hybrid marine power plants. First, architecture of the researched marine power plant is briefly discussed and a simple plant model is presented. The generator can be used to charge the batteries when the ship works with low power demands. Conversely, this battery energy can be used as an additional power source to drive the propulsion or assist the generators when necessary. In addition, energy losses through braking can be recuperated and stored in the battery for later use. Second, the OCS is developed based on equivalent fuel consumption minimisation (EFCM) approach to manage efficiently the power flow between the power sources. This helps the generators to work at the optimal operating conditions, conserving fuel and lowering emissions. In principle, the EFCM is based on the simple concept that discharging the battery at present is equivalent to a fuel burn in the future and vice-versa and, is suitable for real-time implementation. However, instantaneously regulating the power sources’ demands could affect the system stability as well as the lifetime of the components. To overcome this drawback and to achieve smooth energy management, the OCS is designed with a number of penalty factors by considering carefully the system states, such as generators’ fuel consumption and dynamics (stop/start and cranking behaviour), battery state of charge and power demands. Moreover, adaptive energy conversion factors are designed using artificial intelligence and integrated in the OCS design to improve the management performance. The system therefore is capable of operating in the highest fuel economy zone and without sacrificing the overall performance. Furthermore, a real-time simulation platform has been developed for the future investigation of the control logic. The effectiveness of the proposed OCS is then verified through numerical simulations with a number of test cases.

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“…For these reasons, several research works have been pushed by industry to develop electric‐vehicles. This research aims at optimize the cost and energy of the electric powertrain 1,2 . In this context, an electric powertrain is generally composed of one or more electric motors, a power converter, and a measuring chain and instrumentation.…”

Section: Introductionmentioning

confidence: 99%

“…This research aims at optimize the cost and energy of the electric powertrain. 1,2 In this context, an electric powertrain is generally composed of one or more electric motors, a power converter, and a measuring chain and instrumentation. In the electric vehicle motorization, induction motors are widely used due to their convenience in terms of robustness, compactness, reliability, and cost.…”

mentioning

confidence: 99%

Direct torque control scheme for nine switches inverter fed two induction motors‐based more electric vehicle powertrains

Abbache

Tabbache

Douida

et al. 2021

Int Trans Electr Energ Syst

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This paper deals with a direct torque control for nine switches inverter fed two induction motors-based electric vehicles (EVs). In EVs application, the developed system will decrease the installation cost and weight (power electronic devices, position sensors, and mechanical differential). In this context, an adaptive direct torque control of nine switches Inverter which feeds two induction motors is proposed in order to ensure a separate control of two driving wheels and stability for the vehicle when cornering or under slippery road conditions. The experimental tests using dSPACE 1104 card are carried-out to demonstrate the feasibility and effectiveness of the proposed control solution, in terms of robustness and stability.electric vehicle, induction motor, direct torque control, nine switches inverter, dSPACE 1104 | INTRODUCTIONRecently, the strong growth of the transport sector is inevitable in order to satisfy the ever-increasing needs of rapid move or travel. With the growing problems of global warming, pollution, and the depletion of fossil resources, internal combustion engines are no longer suitable for transportation systems and new directions are needed. 1 For these reasons, several research works have been pushed by industry to develop electric-vehicles. This research aims at optimize the cost and energy of the electric powertrain. 1,2 In this context, an electric powertrain is generally composed of one or more electric motors, a power converter, and a measuring chain and instrumentation. In the electric vehicle motorization, induction motors are widely used due to their convenience in terms of robustness, compactness, reliability, and cost. 3 In order to ensure more maneuverability and good driving force distribution, the two driving wheel structure of electric vehicle turns out to be the most suitable. In addition, this structure offers the possibility to eliminate the LIST OF SYMBOLS AND ABBREVIATIONS: DTC, direct torque control; EV, electric vehicle; IGBT, isolated gate bipolar transistor; IFOC, indirect field oriented control; ref, reference quantity; L A,B,C , inverter power legs; S A , B,C , inverter power switches; S L,M,U , lower, medium, and upper power switches; s, stator index; r, rotor index; u, i, voltage, current; U DC , direct voltage; U s , stator voltage vector; ψ s , ψ 0 s , stator flux of both induction motors; Γ e , Γ 0 e , torque of both induction motors; d Γ , d Γ 0 , torque errors of both motors; d ψ , d ψ 0 , flux errors of both motors; α, β, synchronous reference frame index; a, b, c, three phases reference frame index; S (1,…6) , sector number; T s , sampling time; ω m , induction motor speed; ω r , rotor electric speed; R s , stator resistance; L m , inductance (magnetizing inductance); L r , rotor inductance; L s , stator inductance; p, pole-pair number.

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Optimisation-based control for electrified vehicles: challenges and opportunities

Cited by 13 publications

References 53 publications

A SWOT Analysis of the UK EV Battery Supply Chain

A SWOT Analysis of the UK EV Battery Supply Chain

Optimal Control and Real-Time Simulation of Hybrid Marine Power Plants

Direct torque control scheme for nine switches inverter fed two induction motors‐based more electric vehicle powertrains

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