Convex Optimization Methods for Powertrain Sizing of Electrified Vehicles by Using Different Levels of Modeling Details

Pourabdollah, Mitra; Egardt, Bo; Murgovski, Nikolce; Grauers, Anders

doi:10.1109/tvt.2017.2767201

Cited by 58 publications

(32 citation statements)

References 39 publications

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“…A model for energy harvesting was introduced in [17] for analyzing the network capacity of electromagnetic nanonetworks in the THz band. Recently, performance maximization has been typically formulated and solved as a convex optimization problem [18]. However, a practical data transmission system is typically a non-convex utility function.…”

Section: Related Workmentioning

confidence: 99%

“…(33) is a mixed-integer non-linear programming (MINLP) problem, which is typically difficult to solve. Two approximate methods were proposed for the sub-optimal solution of MINLP, namely, 1) the continuous convex approximation [17] and 2) the branch-and-bound method [18]. In this study, because of the complexity of the system, it is difficult to convert Eq.…”

Section: Resource Allocation Problemmentioning

confidence: 99%

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Optimal Haptic Communications Over Nanonetworks for E-Health Systems

Feng

Ali

Iqbal

et al. 2019

IEEE Trans. Ind. Inf.

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Tactile Internet-based nanonetwork is an emerging field that promises a new range of e-health applications, in which human operators can efficiently operate and control devices at the nanoscale for remote-patient treatment. Haptic feedback is inevitable for establishing a link between the operator and unknown in-body environment. However, haptic communications over the terahertz band may incur significant path loss due to molecular absorption. In this paper, we propose an optimization framework for haptic communications over nanonetworks, in which in-body nano-devices transmit haptic information to an operator via the terahertz band. By considering the properties of the terahertz band, we employ Brownian motion to describe the mobility of the nano-devices and develop a time-variant terahertz channel model. Furthermore, based on the developed channel model, we construct a stochastic optimization problem for improving haptic communications under the constraints of system stability, energy consumption, and latency. To solve the formulated non-convex stochastic problem, an improved timevarying particle swarm optimization algorithm is presented, which can deal with the constraints of the problem efficiently by reducing the convergence time significantly. The simulation results validate the theoretical analysis of the proposed system.

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Section: Related Workmentioning

confidence: 99%

Section: Resource Allocation Problemmentioning

confidence: 99%

Optimal Haptic Communications Over Nanonetworks for E-Health Systems

Feng

Ali

Iqbal

et al. 2019

IEEE Trans. Ind. Inf.

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“…Dynamic programming is considered as the global optimisation method; however, it requires large computational effort and is impossible for online applications [18]. Particle swarm optimisation (PSO) [19,20], nondominated sorting genetic algorithms (NSGA-III) [21], and convex optimisation [22] have been developed to achieve acceptable optimisation results in a much faster manner. Offline optimisation cannot guarantee the optimum vehicle performance in real-world driving since the standard driving cycles cannot fully include all scenarios in real-world driving.…”

Section: Introductionmentioning

confidence: 99%

Heuristic action execution for energy efficient charge-sustaining control of connected hybrid vehicles with model-free double Q-learning

Shuai

Zhou

et al. 2020

Applied Energy

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Where a licence is displayed above, please note the terms and conditions of the licence govern your use of this document. When citing, please reference the published version. Take down policy While the University of Birmingham exercises care and attention in making items available there are rare occasions when an item has been uploaded in error or has been deemed to be commercially or otherwise sensitive.

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“…The analysis and modeling consist of an iterating process to validate mathematical models. Mechanical load requirements should be defined from a driving cycle [4,21,25]. There are standardized drive cycles for some kind of vehicles and routes.…”

Section: Introductionmentioning

confidence: 99%

“…Electric motors are the electromechanical interface among electrical and mechanical systems. Both, electrical and mechanical components, are modeled individually and then integrated into a powertrain model [4,8,11,21,25]. As a first approach, simplified models are preferred due to the short simulation time, since they mainly involve converter and motors models with constant efficiency.…”

Section: Introductionmentioning

confidence: 99%

Light electric vehicle powertrain: Modeling, simulation, and experimentation for engineering students using PSIM

Vidal‐Bravo

Cruz-Soto

Paternina

et al. 2020

Comp Applic In Engineering

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Electric transport has been gaining more interest and importance in the last years. Moreover, the variety of transport systems driven by an electric motor has also been increased. Therefore, it is very important to provide engineering students with solid and comprehensible knowledge, as well as handly tools, for modeling an electric traction system. So far, this has been a difficult task for undergraduate students due to a variety of subjects involved, such as electric machines, power converters, control systems, and load estimations. This work is intended to provide a detailed and comprehensible description of the analysis, modeling, and implementation of a powertrain of a light utility vehicle using power electronics simulation (PSIM) commercial software in order that the student acquires the required knowledge for analyzing multiple configurations in the powertrain.

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Convex Optimization Methods for Powertrain Sizing of Electrified Vehicles by Using Different Levels of Modeling Details

Cited by 58 publications

References 39 publications

Optimal Haptic Communications Over Nanonetworks for E-Health Systems

Optimal Haptic Communications Over Nanonetworks for E-Health Systems

Heuristic action execution for energy efficient charge-sustaining control of connected hybrid vehicles with model-free double Q-learning

Light electric vehicle powertrain: Modeling, simulation, and experimentation for engineering students using PSIM

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