Depleting Mode Control Strategies for Plug-in Hybrid Electric Vehicles

2011 ◽  
Vol 130-134 ◽  
pp. 2211-2215
Author(s):  
Bing Zhan Zhang ◽  
Han Zhao ◽  
An Dong Yin
Keyword(s):  
Electric Vehicles ◽  
Fuel Economy ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Control Strategies ◽  
Great Influence ◽  
Torque Control ◽  
Drive Cycle ◽  
Vehicle Simulation ◽  
Hybrid Electric

Control strategy is the most important issue in the Plug-in Hybrid electric vehicles (PHEV) design, which has two modes: charge depleting mode (CD) and charge sustaining mode (CS). The different control strategies in depleting mode will have a great influence on PHEV dynamic performance and fuel economy. The engine optimal torque control strategy was proposed in the paper. The vehicle simulation model in Powertrain Systems Analysis Toolkit (PSAT) was adopted to evaluate the proposed control strategy. The aggressive highway drive cycle Artemis_hwy and a random drive cycle generated by Markov Process were used. The simulation results indicate the proposed control strategy has great improvement in fuel economy.

scholarly journals A Control Strategy for Driving Mode Switches of Plug-in Hybrid Electric Vehicles

2018 ◽  
Vol 10 (11) ◽  
pp. 4237 ◽  
Author(s):  
Yuping Zeng ◽  
Zhikai Huang ◽  
Yang Cai ◽  
Yonggang Liu ◽  
Yue Xiao ◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Dynamic Characteristics ◽  
Duty Cycle ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Torque Ripple ◽  
Torque Control ◽  
Driving Mode ◽  
Wet Clutch ◽  
Hybrid Electric

Driving mode switches of hybrid vehicles are significant events. Due to the different dynamic characteristics of the engine, motor, and wet clutch, it is difficult to coordinate torque fluctuations caused by mode switches. This paper focused on a control strategy for driving mode switches of plug-in hybrid electric vehicles (PHEVs) with a multi-disk wet clutch. First, the dynamic model of the PHEV was established, and a rule-based control strategy was proposed to divide the working mode regions and distribute the torque between engine and motor. Second, the dual fuzzy control strategy for a wet clutch and the coordinated torque control strategy for driving mode switches were proposed. The dual fuzzy logic control system consisted of the initial pulse-width modulation (PWM)’s duty cycle control and the changing rate of the PWM’s duty cycle control. Considering the difference in the dynamic characteristics between engine, motor, and wet clutch, a coordinated control strategy for the driving mode switches of PHEVs was put forward. Third, simulations of driving mode switches between pure electric driving mode and only engine driving mode were conducted. The results showed that the proposed control strategy could reduce the torque ripple and the jerk of the vehicle, completely satisfying the requirements of China. Finally, the control strategy for the motor-assisted engine starting process was tested on the bench. The experiment results indicated that the proposed control strategy was effective.

scholarly journals Powertrain Control for Hybrid-Electric Vehicles Using Supervised Machine Learning

Vehicles ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 267-286 ◽  
Author(s):  
Craig K. D. Harold ◽  
Suraj Prakash ◽  
Theo Hofman
Keyword(s):  
Machine Learning ◽  
Dynamic Programming ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Supervised Machine Learning ◽  
Test Case ◽  
Drive Cycle ◽  
Powertrain Control ◽  
Hybrid Electric

This paper presents a novel framework to enable automatic re-training of the supervisory powertrain control strategy for hybrid electric vehicles using supervised machine learning. The aim of re-training is to customize the control strategy to a user-specific driving behavior without human intervention. The framework is designed to update the control strategy at the end of a driving task. A combination of dynamic programming and supervised machine learning is used to train the control strategy. The trained control strategy denoted as SML is compared to an online-implementable strategy based on the combination of the optimal operation line and Pontryagin’s minimum principle denoted as OOL-PMP, on the basis of fuel consumption. SML consistently performed better than OOL-PMP, evaluated over five standard drive cycles. The EUDC performance was almost identical while on FTP75 the OOL-PMP consumed 14.7% more fuel than SML. Moreover, the deviation from the global benchmark obtained from dynamic programming was between 1.8% and 5.4% for SML and between 5.8% and 16.8% for OOL-PMP. Furthermore, a test-case was conducted to emulate a real-world driving scenario wherein a trained controller is exposed to a new drive cycle. It is found that the performance on the new drive cycle deviates significantly from the optimal policy; however, this performance gap is bridged with a single re-training episode for the respective test-case.

An Investigation on the Effect of Drivetrain Hybridization in a Transit Bus, Series Configuration

2006 ◽  
Author(s):  
Ahmad Khanipour ◽  
Mohsen Esfahanian ◽  
Farhad Sangtarash ◽  
Meisam Amiri
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Control Strategies ◽  
Drive Cycle ◽  
Conventional Vehicle ◽  
Vehicle Engine ◽  
Electric Bus ◽  
Series Configuration ◽  
Hybrid Electric

To achieve higher fuel economy and lower emissions hybridization of conventional vehicles seems to be an effective solution and an important step. In this paper, after a short introduction about the hybrid electric vehicles a brief design of series electric vehicles is introduced. Then one of the Iran-Khodro city buses named O457 is chosen to change to a series hybrid electric bus. After choosing the proper hybrid components the bus performance is investigated to assure whether it can satisfy the required performance or not. Then the conventional O457 and its series configurations for two different control strategies are defined and evaluated using the ADvanced VehIcle SimulatOR, ADVISOR. Simulations are carried out in a combined urban drive cycle because of the lack of a real drive cycle for Tehran city. The fuel consumption and the amount of produced emissions are compared together for three mentioned cases. The validity of simulation has been proved by the close conformity between the value of fuel consumption of the conventional vehicle reported by the company to what has been achieved from the simulation. It is observed that compared to the conventional vehicle, a reduction in fuel consumption about 32% in the maximum SOC control strategy and about 27% in the thermostat control strategy are possible to achieve. In addition, simulation results indicate that air pollution caused by vehicle engine can be greatly reduced through hybridization using each of the mentioned control strategies.

Fuel Efficient Control Strategies for Connected Hybrid Electric Vehicles in Urban Roads

2015 ◽  
Author(s):  
Runing Lin ◽  
Baisravan HomChaudhuri ◽  
Pierluigi Pisu
Keyword(s):  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Control Strategies ◽  
Hierarchical Control ◽  
Control Architecture ◽  
Urban Road ◽  
Hierarchical Control Architecture ◽  
Efficient Control ◽  
Hybrid Electric

This paper presents a fuel efficient control strategy for a group of connected hybrid electric vehicles (HEVs) in urban road conditions. A hierarchical control architecture is proposed in this paper where the higher level controller is considered to be a part of the transportation infrastructure while the lower level controllers are considered to be present in every HEV. The higher level controller uses model predictive control strategy to evaluate the energy efficient velocity profiles for every vehicle for a given horizon. Each lower level controller then tracks its velocity profile (obtained from the higher level controller) in a fuel efficient fashion using equivalent consumption minimization strategy (ECMS). In this paper, the vehicles are modeled in Autonomie software and the simulation results provided in the paper shows the effectiveness of our proposed control architecture.

scholarly journals A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Aishwarya Panday ◽  
Hari Om Bansal
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Control Strategies ◽  
Management Strategies ◽  
Energy Optimization ◽  
Hybrid Vehicles ◽  
Power Split ◽  
Hybrid Electric

Presence of an alternative energy source along with the Internal Combustion Engine (ICE) in Hybrid Electric Vehicles (HEVs) appeals for optimal power split between them for minimum fuel consumption and maximum power utilization. Hence HEVs provide better fuel economy compared to ICE based vehicles/conventional vehicle. Energy management strategies are the algorithms that decide the power split between engine and motor in order to improve the fuel economy and optimize the performance of HEVs. This paper describes various energy management strategies available in the literature. A lot of research work has been conducted for energy optimization and the same is extended for Plug-in Hybrid Electric Vehicles (PHEVs). This paper concentrates on the battery powered hybrid vehicles. Numerous methods are introduced in the literature and based on these, several control strategies are proposed. These control strategies are summarized here in a coherent framework. This paper will serve as a ready reference for the researchers working in the area of energy optimization of hybrid vehicles.

scholarly journals Effective optimal control strategy for hybrid electric vehicle with continuously variable transmission

2019 ◽  
Vol 11 (3) ◽  
pp. 168781401882481 ◽  
Author(s):  
Hangyang Li ◽  
Xiaolan Hu ◽  
Bing Fu ◽  
Jiande Wang ◽  
Feitie Zhang ◽  
...  
Keyword(s):  
Cost Function ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Hybrid Electric Vehicles ◽  
Continuously Variable Transmission ◽  
Optimal Control Strategy ◽  
Variable Transmission ◽  
Hybrid Electric

Hybrid electric vehicles equipped with continuously variable transmission show dramatic improvements in fuel economy and driving performance because they can continuously adjust the operating points of the power source. This article proposes an optimal control strategy for continuously variable transmission–based hybrid electric vehicles with a pre-transmission parallel configuration. To explore the fuel-saving potential of the given configuration, a ‘control-oriented’ quasi-static vehicle model is built, and dynamic programming is adopted to determine the optimal torque split factor and continuously variable transmission speed ratio. However, a single-criterion cost function will lead to undesirable drivability problems. To tackle this problem, the main factors affecting the driving performance of a continuously variable transmission–based hybrid electric vehicle are studied. On that basis, a multicriterion cost function is proposed by introducing drivability constraints. By varying the weighting factors, the trade-off between fuel economy and drivability can be evaluated under a predetermined driving cycle. To validate the effectiveness of the proposed method, simulation experiments are performed under four different driving cycles, and the results indicate that the proposed method greatly enhanced the drivability without significantly increasing fuel consumption. Compared to a single-criterion cost function, the use of multiple criteria is more representative of real-world driving behaviour and thus provides better reference solutions to evaluate suboptimal online controllers.

Sign in / Sign up

Export Citation Format

Share Document