Powersplit Hybrid Electric Vehicle Control With Data Dependent Systems Forecasting

2003 ◽  
Author(s):  
Richard T. Nesbitt ◽  
Sudhakar M. Pandit ◽  
Christian M. Muehlfeld
Keyword(s):  
Hybrid Electric Vehicle ◽  
Power Flow ◽  
Current Data ◽  
General Motors ◽  
Time Step ◽  
Test Vehicle ◽  
Conventional Vehicle ◽  
Power Steering ◽  
Drive Motor ◽  
Sample Time

The focus of this paper is on the implementation of Data Dependent Systems (DDS) forecasting in to the control algorithm of the 2001 Michigan Tech Future Truck. The 2001 MTU Future Truck is a 2000 model year Chevrolet Suburban and utilizes a powersplit transmission, which is similar to the Toyota Prius, for its hybrid conversion. The main source of propulsion comes from a General Motors, all aluminum block, 3.5L V-6. In the Future Truck, the accessory current is not directly measured, so it must be calculated from the measured motor current, generator current and battery current. Accessory current is defined as the current used by all of the high voltage components such as the power steering and AC compressor, except the primary drive motor. In order for the vehicle to be charge sustaining, the generator must produce the same amount of power consumed by the accessories and the drive motor. This calculation will only indicate what the accessory load was at the previous sample time and not what the accessory load will be at the current sample time. When it comes to control of the vehicle, this creates a lag, and the controls will undershoot or overshoot the desired accessory current, which creates inefficiencies due to excessive power flow into and out of the battery pack. In order to better understand the accessory load, Data Dependent Systems (DDS) modeling was done on accessory current data collected from the test vehicle, and an AR(26) model was concluded to be adequate, based on the residual sum of squares (RSS) and unified auto-correlations. The DDS modeling of the accessory current also led to the forecasting of the accessory loads. This helps keep battery use to a minimum by allowing the generator to create the correct amount of power, at that time step, to operate the accessories. Accessory draw from the batteries and generator overshoot going into the batteries is minimized and therefore the overall efficiency of the vehicle goes up. The vehicle was tested on a 50-mile circuit including city and highway driving and elevation changes. The results from the test vehicle showed a power savings of 892 kJ/hour which improved the fuel economy by 3 mpg over stock. The charge sustainability of the vehicle was also achieved which means the range of the vehicle is only limited by the fuel mileage, similar to a conventional vehicle.

scholarly journals Objective Rating of the Launch Behavior of Conventional, Hybrid and Electric Vehicles

2021 ◽  
Author(s):  
Christian Dorsch ◽  
Xiao Wang ◽  
Ferit Küçükay
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicle ◽  
Automatic Transmission ◽  
Major Influence ◽  
Important Process ◽  
Dual Clutch Transmission ◽  
Conventional Vehicle ◽  
Objective Rating ◽  
Dynamic Quality

AbstractThe calibration of conventional, hybrid and electric drivetrains is an important process during the development phase of any vehicle. Therefore, to optimize the comfort and dynamic behavior (known as driveability), many test drives are performed by experienced drivers during different driving maneuvers, e.g., launch, re-launch or gear shift. However, the process can be kept more consistent and independent of human-based deviations by using objective ratings. This study first introduces an objective rating system developed for the launch behavior of conventional vehicles with automatic transmission, dual-clutch transmission, and alternative drivetrains. Then, the launch behavior, namely comfort and dynamic quality, is compared between two conventional vehicles, a plug-in hybrid electric vehicle and a battery electric vehicle. Results show the benefits of pure electric drivetrains due to the lack of launch and shifting elements, as well as the usage of a highly dynamic electric motor. While the plug-in hybrid achieves a 10% higher overall rating compared to the baseline conventional vehicle, the pure electric vehicle even achieves a 21% higher overall rating. The results also highlight the optimization potential of battery electric vehicles regarding their comfort and dynamic characteristics. The transitions and the gradient of the acceleration build-up have a major influence on the launch quality.

scholarly journals Event-triggered attack detection and identification in power-electronics-based DC microgrid

2021 ◽  
Author(s):  
Sicheng Gong
Keyword(s):  
Power Flow ◽  
Detection Algorithm ◽  
Power Line ◽  
Current Data ◽  
Attack Detection ◽  
Dc Microgrid ◽  
Detection Mechanism ◽  
Detection And Identification ◽  
Event Triggered ◽  
Identification Strategy

This paper proposes a novel event-triggered attack detection mechanism for converter-based DC microgrid system. Under a distributive network framework, each node collects its neighbours' relative data to regulate its own output for local stabilization. Without power line current data, hardly can an agent directly identify the source of unexpected power flow, especially under an organized attack composed of voltage variations and corresponding deceptive messages. In order to recognize traitors who broadcast wrong data, target at system distortion and even splitting, an efficient attack detection and identification strategy is mandatory. After the attack detector is triggered, each relative agent refuses to trust any received data directly before authentication. Through proposed two-step verification by comparing theoretical estimated signals with received ones, both self sensors and neighbour nodes would be inspected, and the attacker was difficult to hide himself. Through simulation on SIMULINK/PLECS and hardware experiments on dSpace Platform, the effectiveness of proposed detection algorithm has been proved.

A Method of Static Security Analysis Based on Section Topology Relation

2012 ◽  
Vol 614-615 ◽  
pp. 900-906
Author(s):  
Jun Liu ◽  
Ling Ling Pan ◽  
Yi Jun Yu ◽  
Shu Hai Feng ◽  
Feng Li ◽  
...  
Keyword(s):  
Power Flow ◽  
Jacobian Matrix ◽  
Topological Analysis ◽  
Security Analysis ◽  
Current Data ◽  
Data Section ◽  
Dc Power ◽  
Topology Changes ◽  
Static Security ◽  
Partial Factor

In this paper, a calculation method of static security analysis based on section topology relation is proposed. When topological structure of current data section is the same as that of the basecase section, it fully utilizes the factor tables of Jacobian matrix, and inverse matrix information of the basecase data section in rapid filtration of DC power flow. On the contrary, If topology changes compared with the basecase section, it adopts substation partial topological analysis technology as well as the method of partial factor table correction to increase the speed of calculation. Case studies with a practical power system indicate that the proposed method is correct and reasonable.

scholarly journals SUBOPTIMAL SUPERVISORY LEVEL POWER FLOW CONTROL OF A HYBRID ELECTRIC VEHICLE

2005 ◽  
Vol 38 (1) ◽  
pp. 218-223 ◽  
Author(s):  
Kasemsak Uthaichana ◽  
Sorin Bengea ◽  
Raymond DeCarlo
Keyword(s):  
Flow Control ◽  
Electric Vehicle ◽  
Hybrid Electric Vehicle ◽  
Power Flow ◽  
Power Flow Control ◽  
Hybrid Electric

The University of Tennessee EcoCAR 2 Communications, Outreach, Education and STEM Recruiting Program Overview: Year 2

2013 ◽  
Author(s):  
Katelynn M. Routh ◽  
Scott J. Curran ◽  
David K. Irick
Keyword(s):  
Hybrid Electric Vehicle ◽  
Alternative Fuels ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
General Motors ◽  
Outreach Program ◽  
Vehicle Performance ◽  
University Of Tennessee ◽  
The University ◽  
Outreach And Education

The U.S. Department of Energy’s (DOE) Advanced Vehicle Technology Competition (AVTC) series is a long running collegiate vehicle design competition for North American universities. The current three year competition series, known as EcoCAR 2: Plugging In To the Future, has students design and build a hybrid electric vehicle (HEV) that also incorporates alternative fuel. Teams are donated a 2013 Chevrolet Malibu by General Motors to modify. A significant aspect of the competition series is the public outreach and education aspect that leverages the expertise of the students in advanced vehicle technologies and alternative fuels. This also highlights the systems level approach to integrating all aspects of the vehicle to build a vehicle that has the best possible fuel economy, lowest well-to-wheel greenhouse gas emissions and lowest criteria air pollutant emissions while maintaining or exceeding vehicle performance, utility and safety. This paper presents an overview of the University of Tennessee’s (Team Tennessee) EcoCAR 2 outreach program, including core program goals and measures of effectiveness of the program for Year 2 of the competition. The paper focuses on the role that such programs can have on effective science, technology, engineering and mathematics recruiting through an overview of the outreach activities and the integration of hands on activities and partnerships with local schools. The leveraging of outreach and education capabilities with the team’s outreach partners is also highlighted.

Optimization of Fuel Economy of Hybrid Electric Vehicles Using Set Based Dynamic Programming

2014 ◽  
Author(s):  
Nikhil Ramaswamy ◽  
Nader Sadegh
Keyword(s):  
Dynamic Programming ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Optimal Solution ◽  
The State ◽  
State Variables ◽  
Discrete Time System ◽  
Real Time Control ◽  
Time Step ◽  
Hybrid Electric

Dynamic Programming (DP) technique is an effective algorithm to find the global optimum. However when applying DP for finite state problems, if the state variables are discretized, it increases the cumulative errors and leads to suboptimal results. In this paper we develop and present a new DP algorithm that overcomes the above problem by eliminating the need to discretize the state space by the use of sets. We show that the proposed DP leads to a globally optimal solution for a discrete time system by minimizing a cost function at each time step. To show the efficacy of the proposed DP, we apply it to optimize the fuel economy of the series and parallel Hybrid Electric Vehicle (HEV) architectures and the case study of Chevrolet Volt 2012 and the Honda Civic 2012 for the series and parallel HEV’s respectively are considered. Simulations are performed over predefined drive cycles and the results of the proposed DP are compared to previous DP algorithm (DPdis). The proposed DP showed an average improvement of 2.45% and 21.29% over the DPdis algorithm for the series and the parallel HEV case respectively over the drive cycles considered. We also propose a real time control strategy (RTCS) for online implementation based on the concept of Preview Control. The RTCS proposed is applied for the series and parallel HEV’s over the drive cycles and the results obtained are discussed.

scholarly journals Comparative fuel economy, cost and emissions analysis of a novel mild hybrid and conventional vehicles

2017 ◽  
Vol 232 (13) ◽  
pp. 1846-1862 ◽  
Author(s):  
Mohamed Awadallah ◽  
Peter Tawadros ◽  
Paul Walker ◽  
Nong Zhang
Keyword(s):  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Vehicle Emissions ◽  
Low Cost ◽  
Hybrid Vehicles ◽  
Conventional Vehicle ◽  
Driving Cycles ◽  
Hybrid Concept ◽  
The Relationship ◽  
Mild Hybrid

Mild hybrid vehicles have been explored as a potential pathway to reduce vehicle emissions cost-effectively. The use of manual transmissions to develop novel hybrid vehicles provides an alternate route to producing low cost electrified powertrains. In this paper, a comparative analysis examining a conventional vehicle and a mild hybrid electric vehicle is presented. The analysis considers fuel economy, capital and ongoing costs and environmental emissions, and includes developmental analysis and simulation using mathematical models. Vehicle emissions (nitrogen oxides, carbon monoxide and hydrocarbons) and fuel economy are computed, analysed and compared using a number of alternative driving cycles and their weighted combination. Different driver styles are also evaluated. Studying the relationship between the fuel economy and driveability, where driveability is addressed using fuel-economical gear shift strategies. Our simulation suggests the hybrid concept presented can deliver fuel economy gains of between 5 and 10%, as compared to the conventional powertrain.

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