Control Strategy for Hybrid Electric Vehicle Based on Online Driving Pattern Classification

Yao, Zhengyu; Yoon, Hwan‐Sik

doi:10.4271/08-08-02-0006

Cited by 9 publications

(8 citation statements)

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“…where h i ð Þ = 1, if the predicted class label is the same as the real category label, and others h i ð Þ = 0. It can be seen from equation (15) that the accuracy of the identification model proposed in this paper can reach 95.6% on the test set, indicating that the ability of this identification model is good, which can provide a reference for subsequent analysis.…”

Section: Real Vehicle Test Designmentioning

confidence: 79%

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A novel objective evaluation method of drivability for passenger cars considering subjective and objective consistency

Zhou

Guo

Zhang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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In this paper, aiming at the problems that the random mixed working conditions are difficult to identify, the insufficiency of drivability evaluation indicators system and the lack of robustness for the evaluation model, a novel objective evaluation method of drivability for passenger cars is proposed. First, combining the sliding time window method and Naive Bayesian model (NBM), a hybrid working condition recognition model of multi-source sensor information fusion is constructed, and the real vehicle test under random mixed working conditions shows that the accuracy of working condition identification can reach 95.6%. Then, the objective evaluation index for crawling conditions, starting conditions and tip-in conditions are studied according to the suggestions of subjective evaluation engineers, an objective indicator evaluation system considering expert knowledge and information redundancy between indicators is constructed, among them, R-type clustering and principal component analysis (PCA) are used to eliminate the information redundancy between objective indicators. Finally, based on the back propagation (BP) neural network to optimize the fuzzy membership function, an improved fuzzy comprehensive evaluation (Improve-FCE) method considering subjective and objective consistency is designed. Real vehicle test and analysis results demonstrate that the development of intelligent drivability objective evaluation tool (I-DOET) has good reliability and stability, the maximum subjective and objective relative error of the improved FCE model is 5.13%, and the pass rate reaches 93.3%.

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Section: Real Vehicle Test Designmentioning

confidence: 79%

“…In terms of working condition identification, Guse et al, 13 Nigro et al, 14 Yao and Yoon, 15 etc. focused on the analysis of driving status and behavior, which belong to two categories with low dimensions and need to be further expanded.…”

Section: Introductionmentioning

confidence: 99%

A novel objective evaluation method of drivability for passenger cars considering subjective and objective consistency

Zhou

Guo

Zhang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…Reviewing the control strategy for HEVs, the authors in [17] presented control strategies for HEVs depending on different online driving patterns. This study investigates the feasibility of optimising control for different driving patterns, so that the vehicle can maintain a high level of optimality regardless of the driving pattern.…”

Section: Introductionmentioning

confidence: 99%

Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles

Minh

Moezzi

Cýrus

et al. 2022

ASI

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This paper reviews the latest studies of hybrid electric vehicles (HEVs) on modelling, controls, and energy management. HEV dynamics, formulas, calculations, and schemes of vehicle parts, such as battery, converter, electric motor, generator, and HEV Simulink models, are presented. Moreover, simulations of the propulsion operation, regenerative braking system, and vehicle dynamics are conducted. A comprehensive HEV model is built that is simulated on different driving cycles of Federal Test Procedure 75 (FTP75), New York City Cycle (NYCC), Highway Fuel Economy Test (HWFET), and Extra Urban Driving Cycle (EUDC). Data achieved from these simulations were analysed and tested with several fuel regression models to determine the best fuel regression estimation for HEV fuel consumption on the basis of their weights and tire radiuses. The best fuel regression equation is obtained with a determination coefficient R-squared greater than 99%. Lastly, the optimal model and other HEVs models are simulated on different driving cycles to prove that the fuel consumption of our best-fit regression model is the best.

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“…Regarding the control strategy for HEV, the authors of [9] review different rule-based controls and optimization-based controls in order to improve the fuel economy for HEV. Other research on control strategy for clutch engagement during the switching mode of PHEV is presented in [10].…”

Section: Introductionmentioning

confidence: 99%

“…The authors of[7] present control strategy of hydraulic regenerative braking of electrohydraulic HEV. Research on the optimization control of the regenerative braking system of HEV based on electrical variable transmission is introduced in[8].Regarding the control strategy for HEV, the authors of[9] review different rule-based controls and optimization-based controls in order to improve the fuel economy for HEV. Other research on control strategy for clutch engagement during the switching mode of PHEV is presented in[10].…”

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confidence: 99%

Automatic Clutch Engagement Control for Parallel Hybrid Electric Vehicle

et al. 2021

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Automatic clutch engagement control is essential for all kinds of vehicle power transmissions. The controllers for vehicle power transmissions may include model-based or model-free approaches and must provide high transmission efficiency, fast engagement and low jerk. Most vehicle automatic transmissions are using torque converters with transmission efficiencies up to 96%. This paper presents the use of fuzzy logic control for a dry clutch in parallel hybrid electric vehicles. This controller can minimize the loss of power transmission since it can offer a higher transmission efficiency, up to 99%, with faster engagement, lower jerk and, thus, higher driving comfortability with lower cost. Fuzzy logic control is one of the model-free schemes. It can be combined with AI algorithms, neuro networks and virtual reality technologies in future development. Fuzzy logic control can avoid the complex modelling while maintaining the system’s high stability amid uncertainties and imprecise information. Experiments show that fuzzy logic can reduce the clutch slip and vibration. The new system provides 2% faster engagement speed than the torque converter and eliminates 70% of noise and vibration less than the manual transmission clutch.

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Control Strategy for Hybrid Electric Vehicle Based on Online Driving Pattern Classification

Cited by 9 publications

References 0 publications

A novel objective evaluation method of drivability for passenger cars considering subjective and objective consistency

A novel objective evaluation method of drivability for passenger cars considering subjective and objective consistency

Optimal Fuel Consumption Modelling, Simulation, and Analysis for Hybrid Electric Vehicles

Automatic Clutch Engagement Control for Parallel Hybrid Electric Vehicle

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