Personalized Mobile Sensing System Development for Emerging Electric-Drive Vehicles

2012 ◽  
Vol 466-467 ◽  
pp. 1310-1314
Author(s):  
Jie Wu ◽  
Yi He Sun
Keyword(s):  
Electric Drive ◽  
System Development ◽  
Fuel Efficiency ◽  
Electric Energy ◽  
Computing System ◽  
Hybrid Vehicle ◽  
Driving Behavior ◽  
Green Energy ◽  
Mobile Sensing ◽  
Sensing System

Emerging green-energy cyber-physical systems (CPS), in particular electric-drive vehicles (PHEV, HEV, and EV), have demonstrated great potentials to significantly reduce greenhouse gas emissions and the ever-growing dependence on foreign oil. Few studies have focused on the user-specific driving behavior and its significant impact on electric-drive vehicles fuel efficiency, battery system life-cycle and the environment. This paper presents a personalized mobile sensing system development for the emerging green-energy CPS, which captures user’s run-time driving behavior and characterizes its impact on (P)HEV operations. The proposed sensing computing system has been deployed in a number of PHEVs and HEVs, with user studies of four different drivers and over 150 driving trips under various road and traffic conditions. Using the extracted real-world hybrid vehicle and user driving data, we have conducted detailed analytical studies of users’ specific driving patterns and their impacts on hybrid vehicle electric energy and fuel efficiency.

scholarly journals Large-Scale Battery System Development and User-Specific Driving Behavior Analysis for Emerging Electric-Drive Vehicles

Energies ◽  
2011 ◽  
Vol 4 (5) ◽  
pp. 758-779 ◽  
Author(s):  
Jie Wu ◽  
Kun Li ◽  
Yifei Jiang ◽  
Qin Lv ◽  
Li Shang ◽  
...  
Keyword(s):  
Behavior Analysis ◽  
Electric Drive ◽  
Large Scale ◽  
System Development ◽  
Driving Behavior ◽  
Battery System

scholarly journals A Mobile Sensing System for UrbanPM2.5Monitoring with Adaptive Resolution

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Hongjie Guo ◽  
Guojun Dai ◽  
Jin Fan ◽  
Yifan Wu ◽  
Fangyao Shen ◽  
...  
Keyword(s):  
Air Quality ◽  
Meteorological Data ◽  
Computational Cost ◽  
Estimation Method ◽  
Mobile Sensing ◽  
Prototype System ◽  
Adaptive Grids ◽  
Sensing System ◽  
Adaptive Resolution ◽  
Wide Range

This paper develops a mobile sensing system, the first system used in adaptive resolution urban air quality monitoring. In this system, we employ several taxis as sensor carries to collect originalPM2.5data and collect a variety of datasets, including meteorological data, traffic status data, and geographical data in the city. This paper also presents a novel method AG-PCEM (Adaptive Grid-Probabilistic Concentration Estimation Method) to infer thePM2.5concentration for undetected grids using dynamic adaptive grids. We gradually collect the measurements throughout a year using a prototype system in Xiasha District of Hangzhou City, China. Experimental data has verified that the proposed system can achieve good performance in terms of computational cost and accuracy. The computational cost of AG-PCEM is reduced by about 40.2% compared with a static grid method PCEM under the condition of reaching the close accuracy, and the accuracy of AG-PCEM is far superior as widely used artificial neural network (ANN) and Gaussian process (GP), enhanced by 38.8% and 14.6%, respectively. The system can be expanded to wide-range air quality monitor by adjusting the initial grid resolution, and our findings can tell citizens actual air quality and help official management find pollution sources.

Sensitivity and Correlation Analysis and Implications in Scalable Product Family Design for Plug-In Hybrid Electric Vehicles

2015 ◽  
Author(s):  
Zhila Pirmoradi ◽  
G. Gary Wang
Keyword(s):  
Correlation Analysis ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Electric Energy ◽  
Product Family ◽  
Green Energy ◽  
Product Family Design ◽  
Hybrid Electric ◽  
Market Needs ◽  
And Control

Plug-in Hybrid Electric Vehicles (PHEVs) bear great promises for increasing fuel economy and decreasing greenhouse gas emissions by the use of advanced battery technologies and green energy resources. The design of a PHEV highly depends on several factors such as the selected powertrain configuration, control strategy, sizes of drivetrain components, expected range for propulsion purely by electric energy, known as AER, and the assumed driving conditions. Accordingly, design of PHEV powertrains for diverse customer segments requires thorough consideration of the market needs and the specific performance expectations of each segment. From the manufacturing perspective, these parameters provide the opportunity of mass customization because of the high degree of freedom, especially when the component sizes and control parameters are simultaneously assessed. Based on a nonconventional sensitivity and correlation analysis performed on a simulation model for power-split PHEVs in this study, the product family design (PFD) concept and its implications will be investigated, and limitations of PFD for such a complex product along with directions for efficient family design of PHEVs will be discussed.

System Parameter Study for a Light-Weight Series Hydraulic Hybrid Vehicle

2014 ◽  
Author(s):  
Katharina Baer ◽  
Liselott Ericson ◽  
Petter Krus
Keyword(s):  
Fuel Efficiency ◽  
Hybrid Vehicle ◽  
Urban Traffic ◽  
Parameter Study ◽  
Hydraulic Hybrid ◽  
Component Sizing ◽  
Vehicle Propulsion ◽  
System Pressure ◽  
Light Duty Vehicle ◽  
Hydraulic Hybrid Vehicle

Amongst the hybrid vehicle propulsion solutions aiming to improve fuel efficiency, hybrid electric solutions currently receive most attention, especially on the market. However, hydraulic hybrids are an interesting alternative, especially for heavier vehicles due to higher power density which is beneficial if higher masses are moved. As a step towards a comprehensive design framework to compare several possible hydraulic hybrid architectures for a specified application and usage profile, the model of a series hydraulic hybrid vehicle was previously introduced and initially studied concerning component sizing for an exemplary light-duty vehicle in urban traffic. The vehicle is modeled in the Hopsan simulation tool. A comparably straight-forward engine management is used for the vehicle control; both pump and engine controls are based on the hydraulic accumulator’s state-of-charge. The model is developed further with respect to the accumulator component model. Based on that, the influence of several system and component parameters, such as maximum system pressure and engine characteristics, as well as controller parameters on the vehicle’s performance is analyzed. The goal is to allow for more understanding of the system’s characteristics to facilitate future optimization of the system.

scholarly journals Experimental Setup to Characterize Shift Time for High Performance Hybrid Transmissions

2018 ◽  
Author(s):  
Daniel S. Dorsch ◽  
Justin Carrus ◽  
Zongying Xu ◽  
Derrick Xu ◽  
Amos G. Winter ◽  
...  
Keyword(s):  
Electric Drive ◽  
Electric Motor ◽  
High Performance ◽  
Fuel Efficiency ◽  
Rotational Inertia ◽  
Experimental Setup ◽  
Motor Speed ◽  
Hybrid Architectures ◽  
Speed Difference ◽  
Hybrid Transmission

Hybrid vehicles are increasingly common due to fuel efficiency regulations in place worldwide. High performance hybrids have typically been designed with a focus on improving performance, rather than the combination of both performance and efficiency. In order to improve efficiency of high performance cars, new hybrid architectures are necessary. When incorporating an electric motor, careful focus on operational modes allows for removal of certain elements, such as the reverse gear. Additionally, installing an electric motor directly coupled to the transmission without a clutch gives performance benefits, but requires detailed control of motor speed and novel methodology for shifting. In this paper, the design of an experimental setup for the electric drive in a high performance car hybrid transmission is presented. This architecture allows for characterization of synchronizer behavior during two different shifting methodologies. The first methodology is synchronizing a large rotational inertia with a small shaft speed difference (this differs from a gear shift in a traditional transmission with a large speed difference but small inertia). This situation is encountered when coupling an electric motor to the drivetrain, as the inertia of the electric motor is relatively large compared to a transmission layshaft, but the speed difference is small. The second is testing shifting of a synchronizer where dog tooth engagement happens immediately, with no friction cone to match the speed. This type of shifting is possible with precise electric motor speed control, sensing of the dog tooth position, and fast actuation. This methodology eliminates the need for a friction cone in the synchronizers, while maintaining fast gearshifts for performance driving. Our experimental setup for the electric drive in a hybrid transmission will be used to characterize synchronizer performance with these new shifting methodologies. The insights gained from this setup will aid in designing advanced hybrid architectures.

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