Traction-Motor Power Ratio and Speed Trajectory Optimization for Power Split PHEVs Using Route Information

2012 ◽  
Author(s):  
Mahyar Vajedi ◽  
Amir Taghavipour ◽  
Nasser L. Azad
Keyword(s):  
Fuel Consumption ◽  
Trajectory Optimization ◽  
Hybrid Electric Vehicles ◽  
Management Strategies ◽  
Power Ratio ◽  
Motor Power ◽  
Traction Motor ◽  
Power Split ◽  
Route Information ◽  
Road Grade

Plug-in hybrid electric vehicles (PHEVs) are a promising option for future of transportation. They suggest better fuel economy and less emission compared to conventional HEVs. In this work, a method to find the optimum traction-motor power ratio (TMPR) and speed trajectory for a power-split PHEV is proposed in order to minimize the fuel consumption. The traveling path is divided into several segments. Each segment consists of acceleration, constant speed, and deceleration sections. Also, the route information, such as travel distance, traffic data, the maximum permissible speed, and road grade are known in each segment. The results of simulation show a considerable reduction in the fuel consumption for different energy management strategies; up to 8% in CDCS, 12.9% in manual CDCS, and 18.2% in blended strategy, using the proposed optimum TMPR and speed trajectory.

Optimal integrated energy management and shift control in parallel hybrid electric vehicles with dual-clutch transmission

2019 ◽  
Vol 234 (2-3) ◽  
pp. 599-609
Author(s):  
Guoqiang Li ◽  
Daniel Görges
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Weighting Factor ◽  
Engine Torque ◽  
Shift Control ◽  
Parallel Hybrid ◽  
Power Split ◽  
Hc Emissions

This paper addresses the integration of the energy management and the shift control in parallel hybrid electric vehicles with dual-clutch transmission to reduce the fuel consumption, decrease the pollutant emissions, and improve the driving comfort simultaneously. Dynamic programming with a varying weighting factor in the cost function is proposed to balance the shift frequency and the fuel consumption for the power-split control and gear schedule design. Simulation results present that the drivability can be improved with a varying weighting factor due to fewer shift events while the fuel consumption is only slightly increased compared to dynamic programming with a constant weighting factor. A shift-energy-management strategy integrating the upshift and power-split control based on a multi-objective optimization is presented where model predictive control is employed to ensure engine load rate constraints. The strategy can smoothen the engine torque through torque compensation from the electric motor to prevent engine transient emissions resulting from a sudden load change. In a simulation study, the NOx and HC emissions could be reduced by 1.4% and 2.6% with 2% increase of the overall fuel consumption for the Federal Test Procedure 75 by smoothening the engine torque. For the New European Driving Cycle, 0.9% and 1.1% reduction of NOx and HC emissions could be achieved with only 0.3% more fuel consumption.

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 Modeling and Integrated Optimization of Power Split and Exhaust Thermal Management on Diesel Hybrid Electric Vehicles

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7505
Author(s):  
Jinghua Zhao ◽  
Yunfeng Hu ◽  
Fangxi Xie ◽  
Xiaoping Li ◽  
Yao Sun ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Thermal Management ◽  
Hybrid Electric Vehicle ◽  
Injection System ◽  
Exhaust Pipe ◽  
Exhaust Temperature ◽  
Power Split ◽  
Road Grade ◽  
Total Fuel Consumption ◽  
Hybrid Electric

To simultaneously achieve high fuel efficiency and low emissions in a diesel hybrid electric vehicle (DHEV), it is necessary to optimize not only power split but also exhaust thermal management for emission aftertreatment systems. However, how to coordinate the power split and the exhaust thermal management to balance fuel economy improvement and emissions reduction remains a formidable challenge. In this paper, a hierarchical model predictive control (MPC) framework is proposed to coordinate the power split and the exhaust thermal management. The method consists of two parts: a fuel and thermal optimized controller (FTOC) combining the rule-based and the optimization-based methods for power split simultaneously considering fuel consumption and exhaust temperature, and a fuel post-injection thermal controller (FPTC) for exhaust thermal management with a separate fuel injection system added to the exhaust pipe. Additionally, preview information about the road grade is introduced to improve the power split by a fuel and thermal on slope forecast optimized controller (FTSFOC). Simulation results show that the hierarchical method (FTOC + FPTC) can reach the optimal exhaust temperature nearly 40 s earlier, and its total fuel consumption is also reduced by 8.9%, as compared to the sequential method under a world light test cycle (WLTC) driving cycle. Moreover, the total fuel consumption of the FTSFOC is reduced by 5.2%, as compared to the fuel and thermal on sensor-information optimized controller (FTSOC) working with real-time road grade information.

scholarly journals Navigation Application Programming Interface Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles

2018 ◽  
Vol 2672 (25) ◽  
pp. 139-149 ◽  
Author(s):  
Lei Zhu ◽  
Jacob R. Holden ◽  
Jeffrey D. Gonder
Keyword(s):  
Fuel Consumption ◽  
Large Scale ◽  
Hybrid Electric Vehicles ◽  
Application Programming Interface ◽  
Fuel Saving ◽  
Data Set ◽  
Global Positioning ◽  
Application Programming ◽  
Road Grade ◽  
Programming Interface

The green-routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation application programming interface (API), route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). Navigation APIs, such as Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin–destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption models are built by assigning travel from many global positioning system driving traces to the links in TomTom MultiNet and road grade data from the U.S. Geological Survey elevation data set. Fuel consumption on a link is computed by the proposed model. This paper envisions two kinds of applications: (1) identifying alternate routes that save fuel, and (2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey global positioning system trajectory data set is conducted. The fuel consumption and savings of CVs and HEVs are investigated. At the same time, the trade-off between fuel saving and travel time due to choosing different routes is also examined for both powertrains.

Optimal control of a novel uninterrupted multi-speed transmission for hybrid electric mining trucks

2019 ◽  
Vol 233 (12) ◽  
pp. 3235-3245 ◽  
Author(s):  
Weiwei Yang ◽  
Jiejunyi Liang ◽  
Jue Yang ◽  
Nong Zhang
Keyword(s):  
Dynamic Programming ◽  
Real Time ◽  
Control Strategy ◽  
Dynamic Models ◽  
Fuel Efficiency ◽  
Real Time Control ◽  
Traction Motor ◽  
Time Control ◽  
Power Split ◽  
Shift Strategy

Considering the energy consumption and specific performance requirements of mining trucks, a novel uninterrupted multi-speed transmission is proposed in this paper, which is composed of a power-split device, and a three-speed lay-shaft transmission with a traction motor. The power-split device is adapted to enhance the efficiency of the engine by adjusting the gear ratio continuously. The three-speed lay-shaft transmission is designed based on the efficiency map of traction motor to guarantee the drivability. The combination of the power-split device and three-speed lay-shaft transmission can realize uninterrupted gear shifting with the proposed shift strategy, which benefits from the proposed adjunct function by adequately compensating the torque hole. The detailed dynamic models of the system are built to verify the effectiveness of the proposed shift strategy. To evaluate the maximum fuel efficiency that the proposed uninterrupted multi-speed transmission could achieve, dynamic programming is implemented as the baseline. Due to the “dimension curse” of dynamic programming, a real-time control strategy is designed, which can significantly improve the computing efficiency. The simulation results demonstrate that the proposed uninterrupted multi-speed transmission with dynamic programming and real-time control strategy can improve fuel efficiency by 11.63% and 8.51% compared with conventional automated manual transmission system, respectively.

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