An ANFIS-Based ECMS for Energy Optimization of Parallel Hybrid Electric Bus

Tian, Xiang; Ren, He; Sun, Xiaodong; Cai, Yingfeng; Xu, Yiqiang

doi:10.1109/tvt.2019.2960593

Cited by 79 publications

(54 citation statements)

References 53 publications

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“…Better performance in terms of fuel economy and accuracy was provided. Further, an adaptive neuro-fuzzy reasoning system was combined with the equivalent power consumption minimization strategy, and a practical adaptive energy management strategy for parallel hybrid buses was proposed [66]. The results showed that the fuel economy was improved by this control strategy.…”

Section: Parallel Hybrid Powertrainmentioning

confidence: 99%

Review and Development of Electric Motor Systems and Electric Powertrains for New Energy Vehicles

et al. 2021

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This paper presents a review on the recent research and technical progress of electric motor systems and electric powertrains for new energy vehicles. Through the analysis and comparison of direct current motor, induction motor, and synchronous motor, it is found that permanent magnet synchronous motor has better overall performance; by comparison with converters with Si-based IGBTs, it is found converters with SiC MOSFETs show significantly higher efficiency and increase driving mileage per charge. In addition, the pros and cons of different control strategies and algorithms are demonstrated. Next, by comparing series, parallel, and power split hybrid powertrains, the series–parallel compound hybrid powertrains are found to provide better fuel economy. Different electric powertrains, hybrid powertrains, and range-extended electric systems are also detailed, and their advantages and disadvantages are described. Finally, the technology roadmap over the next 15 years is proposed regarding traction motor, power electronic converter and electric powertrain as well as the key materials and components at each time frame.

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Section: Parallel Hybrid Powertrainmentioning

confidence: 99%

Review and Development of Electric Motor Systems and Electric Powertrains for New Energy Vehicles

et al. 2021

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“…The motor is a three-phase asynchronous motor that can be used as a traction motor to provide torque and also as generator to charge the battery. Therefore, the motor power P m can be expressed as [13]:…”

Section: Motor Modelmentioning

confidence: 99%

“…By introducing a penalty function, the strategy has good power retention characteristics, which makes it more suitable for energy management in the power retention stage of plug-in hybrid electric vehicles [12]. Tian et al [13] proposed an adaptive energy management system composed of offline and online parts to improve the energy efficiency of parallel hybrid electric buses. Therefore, it has been widely studied.…”

Section: Introductionmentioning

confidence: 99%

An ECMS for Multi-Objective Energy Management Strategy of Parallel Diesel Electric Hybrid Ship Based on Ant Colony Optimization Algorithm

Xiang

Yang

2021

Energies

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In order to reduce fuel consumption and reduce the deviation between the final battery state-of-charge (SOC) value and the target value at the same time, a novel double-layer multi-objective optimization method is proposed, which adopts an improved ant colony optimization (ACO) algorithm and the equivalent fuel consumption minimization strategy (ECMS) considering mode switching. The proposed strategy adopts a two-layer structure. In the inner layer, the ECMS considering mode switching was adopted to optimize the working mode and working point, so as to achieve the goal of reducing fuel consumption. In the outer layer, aiming at the shortcomings of traditional ACO, the heuristic factor and adaptive volatilization factor were introduced. An improved ACO method was proposed to optimize the equivalent factor, so as to achieve the goal of reducing the deviation between the final value of SOC and the target value. In order to verify the effectiveness of the proposed algorithm, it is compared with the traditional ECMS strategy and the rule-based (RB) ECMS strategy. The simulation results show that the proposed energy management strategy combining an improved ACO algorithm with ECMS considering mode switching can reduce the energy consumption of the whole ship and control the battery power.

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“…Where r is the wheel radius, T fb represents the total braking torque, f is the rolling resistance coefficient, A represents vehicle frontal area, C d is the drag coefficient of air, g is acceleration of gravity, a represents the road gradient, v is vehicle speed. Based on equation 7, (14), and (17), the driveline simulation model shown in Figure 3 is built using Powertrain Blockset and Vehicle Dynamics Blockset in MATLAB-Simulink (the power-split device is highlighted in the dashed box).…”

Section: Powertrain System Modelingmentioning

confidence: 99%

“…11 The optimization-based control strategies mainly include dynamic programming (DP), equivalent fuel consumption minimization strategy (ECMS), model predictive control (MPC), and deep reinforcement learning algorithm that have emerged with artificial intelligence in recent years. [12][13][14][15] Compared with the rule-based control strategies, the optimization-based control strategies don't need to divide the operation modes for the vehicle, the optimal or sub-optimal solution of the control can be obtained. Therefore, the fuel-saving effect is more obvious.…”

Section: Introductionmentioning

confidence: 99%

Modeling and energy management strategy research of a power-split hybrid electric vehicle

Zou

Huang

et al. 2014

Advances in Mechanical Engineering

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A power-split hybrid electric vehicle with a dual-planetary gearset is researched in this paper. Based on the lever analogy method of planetary gearsets, the power-split device is theoretically modeled, and the driveline simulation model is built by using vehicle modeling and simulation toolboxes in MATLAB. Six operation modes of the vehicle are discussed in detail, and the kinematic constraint behavior of power sources are analyzed. To verify the rationality of the modeling, a rule-based control strategy (RB) and an adaptive equivalent consumption minimization strategy (A-ECMS) are designed based on the finite state machine and MATLAB language respectively. In order to demonstrate the superiority of A-ECMS in fuel-saving and to explore the impact of different energy management strategies on emission, fuel economy and emission performance of the vehicle are simulated and analyzed under UDDS driving cycle. The simulation results of the two strategies are compared in the end, shows that the modeling is rational, and compared with RB strategy, A-ECMS ensures charge sustaining better, enables power sources to work in more efficient areas, and improves fuel economy by 8.65%, but significantly increases NOx emissions, which will be the focus of the next research work.

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An ANFIS-Based ECMS for Energy Optimization of Parallel Hybrid Electric Bus

Cited by 79 publications

References 53 publications

Review and Development of Electric Motor Systems and Electric Powertrains for New Energy Vehicles

Review and Development of Electric Motor Systems and Electric Powertrains for New Energy Vehicles

An ECMS for Multi-Objective Energy Management Strategy of Parallel Diesel Electric Hybrid Ship Based on Ant Colony Optimization Algorithm

Modeling and energy management strategy research of a power-split hybrid electric vehicle

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