Real-Time Energy Management Strategy of Hydrogen Fuel Cell Hybrid Electric Vehicles Based on Power Following Strategy–Fuzzy Logic Control Strategy Hybrid Control
Abstract
:1. Introduction
2. Fuel Cell Hybrid System Architecture and Modelling
2.1. Fuel Cell Hybrid System Architecture
2.2. Fuel Cell Model
2.3. Lithium Battery Model
2.4. Drive Motor Model
2.5. Vehicle Dynamics Modelling
3. Hybrid Energy Management Strategies
3.1. Power Following Strategy
3.1.1. Control Strategy in Drive Mode
- 1.
- When the SOC value is lower than the minimum SOC value
- 2.
- When the SOC value is the ideal SOC value
- 3.
- When the SOC value is higher than the maximum SOC value
3.1.2. Control Strategy in Braking Mode
- Fuel cell turn-on and turn-off control module: handling the start–stop process of a fuel cell;
- Source-generated power calculation module: based on the vehicle’s demanded pow-er , the demanded output power of the fuel cell before regulation is calculated;
- SOC power correction module: regulating the demanded output power of the fuel cell;
- Fuel cell operating-point-determination module: it is mainly responsible for protecting the fuel cell, limiting the power output, making it work in the region of high efficiency, improving the life of the fuel cell and ensuring its normal operation.
3.2. Shortcomings of the PFS
3.3. PFS-FLCS Hybrid Strategy
4. Experiments and Analyses
4.1. Simulation Model Building
4.2. Selection of Simulation Conditions and Dynamics Validation
4.3. Comparison and Analysis of Simulation Results
5. Conclusions and Outlook
- The proposed PFS-FLCS hybrid energy management strategy can meet the requirements of vehicle dynamics and can achieve speed following for WLTC, and the PFS-FLCS hybrid control strategy has a smaller range of SOC fluctuation degree and a smoother SOC output compared with the FLCS and PFS, which avoids a wide range of fluctuation of the battery’s SOC and is of great significance for extending the service life of the battery.
- The proposed PFS-FLCS hybrid energy management control strategy distributes the working points of the fuel cell in the high-efficiency zone by using an FLCS to adjust the correction coefficients in real time, which reduces the hydrogen consumption during the driving process and is of great importance to improve the economy of the whole vehicle.
- Compared with PFS and FLCS, the output power variability of the fuel cell based on the PFS-FLCS strategy is reduced by 14.6% and 5.1%, respectively, which is conducive to prolonging the service life of the fuel cell and improving its durability. Its 100 km hydrogen consumption is reduced by 13.5% and 4.1%, respectively, so the energy management strategy based on the PFS-FLCS hybrid control can significantly improve the overall vehicle economy.
- In this paper, the simulation verification of the PFS-FLCS is completed only under WLTC driving conditions, and it is hoped that the simulation verification analysis can be carried out under other typical conditions, which will improve the applicability of the hybrid strategy. The validation analysis of each energy management strategy is limited to the simulation level, and a future research work is expected to be able to carry out the hardware-in-the-loop simulation of the whole vehicle.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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EMS | Advantages | Shortcomings |
---|---|---|
control strategies based on global optimisation [9,10,11]. | the control is so effective and precise that global control optimisation can be achieved. | high computational effort and poor real-time performance. |
control strategies based on transient optimisation [13,14,15]. | realise real-time optimal control with good control effect. | computationally intensive and expensive to run. |
rule-based control strategies [16,17,18]. | simple design, low computational effort and good real-time performance. | rule-making relies on the experience of engineers [19,20]. |
Indexes | Restrictive Condition |
---|---|
acceleration time 0–100 km/h | ≤17 s (the car is fully loaded) |
maximum vehicle speed | ≥130 km/h (the car is fully loaded) |
climbing capacity of vehicles | ≥20% (the car is fully loaded and travelling at 30 km/h) |
Name of Structure | Parametric | Parameter Value |
---|---|---|
vehicle component | vehicle mass | 1875 |
windward side | 2.385 | |
atmospheric drag coefficient | 0.3 | |
wheelbases | 2.670 | |
tires | tyre rolling radius | 0.298 |
rolling resistance coefficient | 0.015 | |
drive motor | maximum power | 90 |
rated power | 40 | |
peak efficiency | 0.97 | |
fuel cell | maximum power | 40 |
peak efficiency | 0.59 | |
li-ion battery | battery capacity | 20 |
number of tandem connections | 30 |
Workspace Number | Workspace [] | Midpoint of a Range |
---|---|---|
1 | 0–5556 | 2778 |
2 | 5556–7407 | 6481.5 |
3 | 7407–15,185 | 11,296 |
4 | 15,185–24,074 | 19,629.5 |
5 | 24,074–30,444 | 27,259 |
6 | 30,444–38,519 | 34,481.5 |
7 | 38,519–40,000 | 39,259.5 |
Calibration Coefficient | Fuel Cell Output Power before SOC Correction | |||||||
---|---|---|---|---|---|---|---|---|
Module Name | Module Meaning |
---|---|
drive cycle<cyc> | recirculation condition |
<sdo>fuel cell | data output module |
<vc>fuel cell | vehicle control module |
vehicle<veh> | vehicle module |
wheel and axle<wh> | wheel and half shaft modules |
final drive<fd> | main reducer module |
gearbox<gb> | transmission module |
motor/controller<mc> | motor and control modules |
electric acc loads<acc> | battery pack accessory modules |
power bus<pb> | power bus module |
energy storage<ess> | battery storage module |
PFS-FLCS | PFS-FLCS hybrid control strategy module |
fuel converter<fc>net model | fuel cell module |
exhaust sys<ex> | emission module |
Energy Management Strategy | Rate of Change of Hydrogen Consumption [%] | PEMFC Output Power Change Rate [%] |
---|---|---|
power following strategy | −13.5 | −14.6 |
fuzzy control strategy | −4.1 | −5.1 |
Simulation Results | Power Following Strategy | Fuzzy Control Strategy | PFS-FLCS Hybrid Control Strategy |
---|---|---|---|
hydrogen consumption [] | 62.2 | 56.1 | 53.8 |
average fuel cell output power [] | 9490.8 | 8466.1 | 8105.2 |
average fuel cell output efficiency [%] | 0.52 | 0.53 | 0.55 |
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Zou, K.; Luo, W.; Lu, Z. Real-Time Energy Management Strategy of Hydrogen Fuel Cell Hybrid Electric Vehicles Based on Power Following Strategy–Fuzzy Logic Control Strategy Hybrid Control. World Electr. Veh. J. 2023, 14, 315. https://doi.org/10.3390/wevj14110315
Zou K, Luo W, Lu Z. Real-Time Energy Management Strategy of Hydrogen Fuel Cell Hybrid Electric Vehicles Based on Power Following Strategy–Fuzzy Logic Control Strategy Hybrid Control. World Electric Vehicle Journal. 2023; 14(11):315. https://doi.org/10.3390/wevj14110315
Chicago/Turabian StyleZou, Ke, Wenguang Luo, and Zhengjie Lu. 2023. "Real-Time Energy Management Strategy of Hydrogen Fuel Cell Hybrid Electric Vehicles Based on Power Following Strategy–Fuzzy Logic Control Strategy Hybrid Control" World Electric Vehicle Journal 14, no. 11: 315. https://doi.org/10.3390/wevj14110315
APA StyleZou, K., Luo, W., & Lu, Z. (2023). Real-Time Energy Management Strategy of Hydrogen Fuel Cell Hybrid Electric Vehicles Based on Power Following Strategy–Fuzzy Logic Control Strategy Hybrid Control. World Electric Vehicle Journal, 14(11), 315. https://doi.org/10.3390/wevj14110315