A Causal and Real-Time Capable Power Management Algorithm for Off-Highway Hybrid Propulsion Systems
Abstract
:1. Introduction
1.1. Motivation
1.2. Classification of Power Management Algorithms
1.3. Requirements for the Off-Highway Application Power Management
- Modular structure
- Real-time capability
- Compatibility to series production propulsion system control units
- Suitability for different mission scenarios and velocity/load control modes (including driver-controlled traction torque demand and automatically controlled drive strategies)
- Consideration of variable auxiliary or external load requests in the PMA.
2. Boundaries of the Simulation Case Study
2.1. Hybrid Diesel Multiple Unit Train (DMU) System Specification
2.2. Drive Strategy
3. System Simulation Model and Validation
3.1. Modelling System Components
3.1.1. Vehicle Model
3.1.2. Engine Model
3.1.3. Gearbox Model
3.1.4. Motor/Generator Model
3.1.5. Battery Model
3.2. Model Validation
3.2.1. Battery Model Validation
3.2.2. Powertrain Model Validation
4. Hybrid Power Management Algorithm (PMA)
4.1. Problem Definition
4.2. Hybrid Operation Modes
4.3. PMA Optimization Routine
4.3.1. Power Vector Definition
4.3.2. Power Split Optimization
4.3.3. Energy Cost Equivalent Charge Factor
4.3.4. SOC Control Function
5. Case Study Results
6. Conclusions and Outlook
Author Contributions
Conflicts of Interest
References
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Vehicle | type | Siemens Desiro VT642 |
number PUs | 2 | |
operating weight | 83,000 kg | |
Engine | type | MTU 6H1800R85LP |
number cylinders | 6 | |
rated power | 390 kW | |
rated speed | 1800 rpm | |
Motor/Generator | type | p. magnet synchron. motor |
rated power | 200 kW (continuous) | |
rated speed | 1600 rpm | |
Gearbox | type | ZF EcoLife |
number gears | 6 | |
Battery | type | Lithium-ion battery |
nom. voltage | 670 V | |
nom. capacity | 90 Ah | |
max./min. current | +/-300 A |
Parameter | Symbol | Unit | Value |
---|---|---|---|
Vehicle mass | kg | 83,000 | |
Track coefficient | - | 0.001 | |
Drag coefficient | - | 0.8 | |
Frontal area | m2 | 10.8 | |
Dynamic roll radius | m | 0.38 | |
Differential ratio | - | 2.59 | |
Differential efficiency | - | 0.95 |
Drive Event | Operation Mode | ||||
---|---|---|---|---|---|
Acceleration | Pure ICE | ++ | ++ | - | 0 |
Combined Mode | ++ | + | + | - | |
Cruising | Pure ICE | + | + | - | 0 |
Pure Electric | + | 0 | + | - | |
Combined Mode | + | + | + | - | |
Charge Mode | + | ++ | - | + | |
Deceleration | Recuperation | -- | + | -- | + |
Halt | Normal Halt | 0 | + | - | 0 |
Start/Stop | 0 | 0 | 0 | - | |
Charge Mode | 0 | + | - | + |
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Schalk, J.; Aschemann, H. A Causal and Real-Time Capable Power Management Algorithm for Off-Highway Hybrid Propulsion Systems. Energies 2017, 10, 10. https://doi.org/10.3390/en10010010
Schalk J, Aschemann H. A Causal and Real-Time Capable Power Management Algorithm for Off-Highway Hybrid Propulsion Systems. Energies. 2017; 10(1):10. https://doi.org/10.3390/en10010010
Chicago/Turabian StyleSchalk, Johannes, and Harald Aschemann. 2017. "A Causal and Real-Time Capable Power Management Algorithm for Off-Highway Hybrid Propulsion Systems" Energies 10, no. 1: 10. https://doi.org/10.3390/en10010010