An optimal power management strategy for power split plug-in hybrid electric vehicles

Taghavipour, Amir; Azad, Nasser L.; McPhee, John

doi:10.1504/ijvd.2012.050085

Cited by 26 publications

(14 citation statements)

References 26 publications

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“…The calibratable build of the ECU enables real-time tuning of controller parameters. Moreover, high-fidelity powertrain models can be modified and re-deployed into the real-time computer very efficiently to accommodate, for example, different HEV architectures and component sizes (for an example, see [4]). Lastly, by employing the real-time battery cycler, real-time model solver, and realistic ECUs, it is possible to simulate the control loop with great accuracy, and without losing any real-time dynamics of the system, which is of great importance in rigorous evaluation of the HEV power management controllers.…”

Section: Hardware-in-the-loop Setupmentioning

confidence: 99%

A battery hardware-in-the-loop setup for concurrent design and evaluation of real-time optimal HEV power management controllers

Razavian

Azad

McPhee

2013

IJEHV

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Abstract:We have developed a battery hardware-in-the-loop (HIL) setup, which can facilitate the process of design and evaluation of power management controllers for hybrid electric vehicles (HEVs) in a novel cost-and time-effective manner. Since the dynamics of the battery greatly affects the HEV power management controller design, and because such dynamic behavior is difficult to model, physical batteries and a real-time battery cycler are included in the setup for greater simulation fidelity. The setup employs a scaled-down battery HIL that reduces the development and testing efforts, while, by using Buckingham's Pi Theorem, maintains the required flexibility and enhances the control loop fidelity.In this article, the application of the setup in integrating the development and the evaluation processes is shown. First, the setup is used for parameter identification of a simple control-oriented model of the battery, which is then used in the power management controller design. Finally, the real-time performance of the designed controller, programmed into an electronic control unit (ECU), is tested with the same setup in the realistic control environment. Furthermore, the battery HIL simulation results show that the designed controller is able to accurately capture the dynamics of the real system, by which the assumptions made in its design process can be confidently justified.

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Section: Hardware-in-the-loop Setupmentioning

confidence: 99%

A battery hardware-in-the-loop setup for concurrent design and evaluation of real-time optimal HEV power management controllers

Razavian

Azad

McPhee

2013

IJEHV

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“…These key elements can be integrated in three different ways: series, parallel and power-split (Taghavipour, Azad, and McPhee 2012). Of these, the power-split configuration takes advantage of the both series and parallel architectures and offers the most flexible and efficient option.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective component sizing of a power-split plug-in hybrid electric vehicle powertrain using Pareto-based natural optimization machines

Mozaffari

Vajedi

Chehresaz

et al. 2015

Engineering Optimization

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The urgent need to meet increasingly tight environmental regulations and new fuel economy requirements has motivated system science researchers and automotive engineers to take advantage of emerging computational techniques to further advance hybrid electric vehicle and plug-in hybrid electric vehicle (PHEV) designs. In particular, research has focused on vehicle powertrain system design optimization, to reduce the fuel consumption and total energy cost while improving the vehicle's driving performance. In this work, two different natural optimization machines, namely the synchronous self-learning Pareto strategy and the elitism non-dominated sorting genetic algorithm, are implemented for component sizing of a specific power-split PHEV platform with a Toyota plug-in Prius as the baseline vehicle. To do this, a high-fidelity model of the Toyota plug-in Prius is employed for the numerical experiments using the Autonomie simulation software. Based on the simulation results, it is demonstrated that Pareto-based algorithms can successfully optimize the design parameters of the vehicle powertrain.

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“…[3], [4] are causal controllers, capable of providing nearoptimal solutions. However, they are computationally expensive, and the results may be inferior to global optimal solutions [4].…”

Section: Introductionmentioning

confidence: 99%

“…[3], [4] are causal controllers, capable of providing nearoptimal solutions. However, they are computationally expensive, and the results may be inferior to global optimal solutions [4]. Pontryagin's Minimum Principle (PMP) is a useful approach for HEV applications, which can result in the global optimal solution under some conditions [5]- [8].…”

Section: Introductionmentioning

confidence: 99%

On real-time optimal control of a series Hybrid Electric Vehicle with an ultra-capacitor

Razavian

Azad

McPhee

2012

2012 American Control Conference (ACC)

Self Cite

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To design a supervisory plan for a Hybrid Electric Vehicle (HEV), different methods are presented in the literature. In many of these controllers, there are a few parameters that must be tuned according to future driving conditions. To address this issue, a novel feedback controller is introduced in this paper that serves as the supervisory plan of a series HEV, and does not require the exact knowledge of the drive cycle. To find this controller, first a mathematical model of the hybrid drivetrain is developed, then Pontryagin's Minimum Principle is applied assuming that the drive cycle is known in advance. Based on the mechanism of the optimal control, a set of mathematical rules is extracted, and an optimal feedback controller is designed. It is also shown that a priori knowledge of the future drive cycle is not required; it is possible to tune the controller parameters, knowing only the cruise time and the available negative energy during braking.

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An optimal power management strategy for power split plug-in hybrid electric vehicles

Cited by 26 publications

References 26 publications

A battery hardware-in-the-loop setup for concurrent design and evaluation of real-time optimal HEV power management controllers

A battery hardware-in-the-loop setup for concurrent design and evaluation of real-time optimal HEV power management controllers

Multi-objective component sizing of a power-split plug-in hybrid electric vehicle powertrain using Pareto-based natural optimization machines

On real-time optimal control of a series Hybrid Electric Vehicle with an ultra-capacitor

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