Hardware-in-the-loop simulation for the design and verification of the control system of a series–parallel hybrid electric city-bus

Wang, Lei; Zhang, Yong; Yin, Chengliang; Hu, Zhang; Wang, Cunlei

doi:10.1016/j.simpat.2012.02.010

Cited by 58 publications

(18 citation statements)

References 22 publications

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“…The methodology is based on models and an HIL platform, following the fault injection approach presented in Section 3.2.2. In the literature, most of the work presented about HIL platforms was focused on the development and validation of new control strategies and embedded units [27][28][29] and in some cases, authors mention the use of such platforms for the analysis of specific faults [30][31][32][33]. Nevertheless, it is difficult to find publications where an HIL platform is used systematically in the analysis of fault modes and effects of a system.…”

Section: Need For a Quantitative Fault Analysis Methodologymentioning

confidence: 99%

Model-Based Fault Analysis for Railway Traction Systems

Olmo¹,

Garramiola²,

Poza³

et al. 2018

Modern Railway Engineering

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Fault analysis in industrial equipment has been usually performed using classical techniques such as failure modes and effects analysis (FMEA) and fault tree analysis (FTA). Model-based fault analysis has been used during the last several years in order to overcome the limitations of classical methods when complex industrial equipment has to be analyzed. In railway and automotive sectors, the development and validation of new products are based on hardware-in-the-loop (HIL) platforms. In this chapter, a methodology to enhance classical FMEAs is presented. Based on HIL simulations, the objective is to improve the results of the fault analysis with quantitative information about the effects of each fault mode. In this way, the impact of the fault analysis in the design of the traction system, the development of new diagnostic functionalities and in the maintenance tasks will increase.

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Section: Need For a Quantitative Fault Analysis Methodologymentioning

confidence: 99%

Model-Based Fault Analysis for Railway Traction Systems

Olmo¹,

Garramiola²,

Poza³

et al. 2018

Modern Railway Engineering

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“…These grids are refined through progressive iterations to achieve the global optimal fuel saving (29.76% compared to RB method) at substantially reduced computational steps and memory requirements [75]. The optimal control strategy found by IDP can be fit to real-time application using Elman NN achieving a suboptimal result of 24.6%.…”

Section: Adaptive Dynamic Programming (Adp)mentioning

confidence: 99%

“…The optimal control strategy found by IDP can be fit to real-time application using Elman NN achieving a suboptimal result of 24.6%. The drawbacks of this method is that the drive cycle is required as a priori and that small changes in traffic or ridership, even for fixed-route buses, can entirely change the driving profile [75].…”

Section: Adaptive Dynamic Programming (Adp)mentioning

confidence: 99%

Towards Optimal Power Management of Hybrid Electric Vehicles in Real-Time: A Review on Methods, Challenges, and State-Of-The-Art Solutions

2018

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Abstract:In light of increasing alerts about limited energy sources and environment degradation, it has become essential to search for alternatives to thermal engine-based vehicles which are a major source of air pollution and fossil fuel depletion. Hybrid electric vehicles (HEVs), encompassing multiple energy sources, are a short-term solution that meets the performance requirements and contributes to fuel saving and emission reduction aims. Power management methods such as regulating efficient energy flow to the vehicle propulsion, are core technologies of HEVs. Intelligent power management methods, capable of acquiring optimal power handling, accommodating system inaccuracies, and suiting real-time applications can significantly improve the powertrain efficiency at different operating conditions. Rule-based methods are simply structured and easily implementable in real-time; however, a limited optimality in power handling decisions can be achieved. Optimization-based methods are more capable of achieving this optimality at the price of augmented computational load. In the last few years, these optimization-based methods have been under development to suit real-time application using more predictive, recognitive, and artificial intelligence tools. This paper presents a review-based discussion about these new trends in real-time optimal power management methods. More focus is given to the adaptation tools used to boost methods optimality in real-time. The contribution of this work can be identified in two points: First, to provide researchers and scholars with an overview of different power management methods. Second, to point out the state-of-the-art trends in real-time optimal methods and to highlight promising approaches for future development.

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“…There are many prototypes of this scheme like Eaton and Volvo. For the parallel-series hybrid vehicle [5,6] as the configuration in Figure 1, the complex mechanical design has prevented its application as a main hybrid topology. As the configuration in Figure 2, the parallel-series scheme is an improvement of series hybrid which adds a clutch between the generator and the motor; thus the engine can drive the vehicle in a proper speed range, and the overall efficiency can be improved compared with the pure series hybrid because the energy conversion process is avoided when the engine drives.…”

Section: Introductionmentioning

confidence: 99%

Parameters Design for a Parallel Hybrid Electric Bus Using Regenerative Brake Model

2014

Advances in Mechanical Engineering

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A design methodology which uses the regenerative brake model is introduced to determine the major system parameters of a parallel electric hybrid bus drive train. Hybrid system parameters mainly include the power rating of internal combustion engine (ICE), gear ratios of transmission, power rating, and maximal torque of motor, power, and capacity of battery. The regenerative model is built in the vehicle model to estimate the regenerative energy in the real road conditions. The design target is to ensure that the vehicle meets the specified vehicle performance, such as speed and acceleration, and at the same time, operates the ICE within an expected speed range. Several pairs of parameters are selected from the result analysis, and the fuel saving result in the road test shows that a 25% reduction is achieved in fuel consumption.

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Hardware-in-the-loop simulation for the design and verification of the control system of a series–parallel hybrid electric city-bus

Cited by 58 publications

References 22 publications

Model-Based Fault Analysis for Railway Traction Systems

Model-Based Fault Analysis for Railway Traction Systems

Towards Optimal Power Management of Hybrid Electric Vehicles in Real-Time: A Review on Methods, Challenges, and State-Of-The-Art Solutions

Parameters Design for a Parallel Hybrid Electric Bus Using Regenerative Brake Model

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