Experimental validation of power distribution control and energy management strategies for hydrogen-electric hybrid power ship
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摘要: 为探究船舶能量管理策略在实际混合动力系统以及复杂工况下的真实性能，基于缩比试验平台测试了3种能量管理策略的性能；以一艘氢电混合动力船为研究对象，借鉴船载能量管理系统特点，设计了既有策略Ⅰ；通过制定8个燃料电池堆栈的启停规则，设计了既有策略Ⅱ以及状态机策略；提出了试验平台缩放方法，模拟了燃料电池系统和蓄电池系统；依据燃料电池的最佳效率点和试验平台特点，设计缩放系数为342.857；在稳态工况和瞬态工况下，基于试验数据分析了功率分配控制性能、效率、能耗、运行压力以及应用特点与局限性。试验结果表明：试验平台的功率分配控制平均偏差在1%以内，可以非常好地跟踪能量管理策略优化后的燃料电池参考功率，其中状态机策略在稳态和瞬态工况实际电流和参考电流的平均绝对偏差分别为0.120%、0.029%；在所提出的3种能量管理策略中，状态机策略在节能和降低燃料电池运行压力方面表现综合最佳，在稳态工况和瞬态工况下，相比既有策略Ⅰ可分别降低2.84%和7.23%氢气消耗，相比既有策略Ⅱ可以分别降低83.00%和84.23%的燃料电池堆栈启停频率；状态机策略下能够使得燃料电池堆栈平均效率维持在52%以上；状态机策略在应用过程面临着燃料电池频繁启停、决策权冲突以及燃料电池性能退化等挑战；所提出的试验方法存在一定局限性，燃料电池模拟设备的响应时间为1 s且存在300 W功率损失，并受到试验环境以及缩放和简化过程的影响；所提出的试验方法与能量管理策略可以用于指导实船高效能量管理策略的研究与应用。Abstract: To investigate the actual performance of ship energy management strategies in practical hybrid power systems under complex operating conditions, three energy management strategies were tested based on a scaled experimental platform. A hydrogen-electric hybrid ship was selected as the research object, and existing characteristics of onboard energy management systems were utilized to design strategy Ⅰ. Additionally, by establishing eight operational rules for the start-stop cycles of fuel cell stacks, strategy Ⅱ and a state machine strategy were developed. A scaling method for the experimental platform was proposed to simulate both fuel cell systems and battery systems. Based on the optimal efficiency point of the fuel cell and the characteristics of the experimental platform, a scaling factor of 342.857 was designed. In both steady-state and transient conditions, the performance of power distribution control, efficiency, energy consumption, operating pressure, as well as application characteristics and limitations, were analyzed based on experimental data. Experimental results indicate that the average deviation of power distribution control on the experimental platform is within 1%, demonstrating a strong capability to track the reference power of the fuel cell optimized by energy management strategies. Specifically, under steady-state and transient conditions, the state machine strategy achieves average absolute deviations between actual current and reference current of 0.120% and 0.029%, respectively. Among the three proposed rule-based energy management strategies, the state machine strategy shows superior overall performance in terms of energy savings and reduction of operational pressure on the fuel cell. In both steady-state and transient conditions, compared to the existing strategy Ⅰ, the state machine strategy reduces hydrogen consumption by 2.84% and 7.23%, respectively, in comparison to the existing strategy Ⅱ, it reduces the frequency of fuel cell stack start-stop cycles by 83.00% and 84.23%, respectively. The state machine strategy maintains the average efficiency of the fuel cell stack above 52%. However, during its application, this strategy faces challenges such as frequent start-stop operations of the fuel cells, conflicts in decision-making authority, and performance degradation of the fuel cells. Additionally, the proposed experimental method has certain limitations; specifically, the response time of the fuel cell simulation equipment is 1 s with a power loss of 300 W, which is also influenced by testing environments as well as scaling and simplification processes. The proposed experimental method and energy management strategy can serve as a guide for the research and application of efficient energy management strategies in actual vessels.
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Key words:
- marine engineering /
- energy management strategy /
- experimental validation /
- hybrid power ship /
- fuel cell /
- battery
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图 2 “三峡氢舟1”航行工况数据
Figure 2. Navigation conditions data of "Three Gorges Hydrogen Boat No.1"
图 4 单个燃料电池堆栈功率-效率特性
Figure 4. Power-efficiency characteristics of a single fuel cell stack
图 6 稳态工况下既有策略结果
Figure 6. Energy management results under steady-state conditions with existing strategies
图 7 稳态工况下状态机策略结果
Figure 7. Results of state machine strategy under steady-state conditions
图 9 瞬态工况下既有策略结果
Figure 9. Experimental results of existing strategies under transient conditions
图 10 瞬态工况下状态机策略结果
Figure 10. Results of state machine strategy under transient conditions
图 11 状态机能量管理策略功率控制结果
Figure 11. Power control results of state machine energy management strategy
图 12 稳态工况效率和能耗
Figure 12. Efficiency and energy consumption under steady-state conditions
图 13 瞬态工况效率与能耗
Figure 13. Efficiency and energy consumption under transient conditions
表 1 “三峡氢舟1”的主要设计参数
Table 1. Key design parameters of "Three Gorges Hydrogen Boat No.1"
参数 值 参数 值 最大船长/m 49.90 燃料电池堆栈额定功率/kW 70 型深/m 3.20 蓄电池组总容量/(kW·h) 903 型宽/m 10.40 燃料电池堆栈数量 8 设计吃水/m 1.85 蓄电池组数量 2 乘客/人 80 推进电机功率/kW 2×500 巡航航速/(km·h-1) 20 最大航速/(km·h-1) 28 氢气储量 35 MPa，≥240 kg 续航力/km 巡航下不少于200 
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表 2 基于试验平台的既有策略Ⅰ
Table 2. Existing strategy Ⅰ based on experimental platform
优先级顺序 模式 案例船单个燃料电池堆栈电流/A 试验平台 单个燃料电池堆栈电流/A 燃料电池系统总电流/A 6 模式0 0 0.000 0.000 5 模式1 100 0.113 0.904 4 模式2 150 0.170 1.360 3 模式3 200 0.227 1.816 2 模式4 250 0.283 2.264 1 模式5 270 0.306 2.449
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表 3 燃料电池堆栈启用数量规则
Table 3. Rules for activation of fuel cell stacks
案例船燃料电池系统总功率规则/kW 试验平台燃料电池系统总功率规则/W 启用数量/个 Pt≤25 Ps≤72.92 0 25 < Pt≤50 72.92 < Ps≤145.83 1 50 < Pt≤100 145.83 < Ps≤291.67 2 100 < Pt≤150 291.67 < Ps≤437.50 3 150 < Pt≤200 437.50 < Ps≤583.33 4 200 < Pt≤250 583.33 < Ps≤729.17 5 250 < Pt≤300 729.17 < Ps≤875.00 6 300 < Pt≤350 875.00 < Ps≤1 020.83 7 350 < Pt 1 020.83 < Ps 8
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表 4 状态机规则
Table 4. State machine rules
S/% 状态 Pd/W Pr/W S>Smax 1 Pd≤P1 P2 2 Pd∈[P1，P2] Pd 3 Pd≥P2 P2 4 Pd＜P3 P3 Smin≤S≤Smax 5 Pd∈[P3，P2] Pd 6 Pd≥P2 P2 S < Smin 7 Pd≤P2 Pd+Pc 8 Pd≥P2 P2
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表 5 关键参数缩放前后对比
Table 5. Comparison of key parameters before and after scaling
编号 关键参数 “三峡氢舟1” 试验平台 说明 1 直流母线电压/V 650 490 模拟直流组网 2 燃料电池系统最小输出功率/kW 15 0.5 用于设计能量管理策略 3 燃料电池系统最优总输出功率/kW 240 0.7 用于设计能量管理策略 4 单个燃料电池堆栈最优输出功率/kW 30 0.087 5 87.5 W=700 W×(240 kW/30 kW) 5 燃料电池系统最大总输出功率/kW 500 1.2 用于设计能量管理策略 6 单个燃料电池堆栈最大输出功率/kW 70 0.168 168 W=1 200 W×(70 kW/500 kW) 7 燃料电池系统最大总输出电流/A 2 160 2.45 2.449 A≈1 200 W/490 V 8 单个燃料电池堆栈最大输出电流/A 270 0.31 0.306 A≈2.449 A×(270 A/2 160 A) 9 蓄电池组最大放电电流/A 100 1.5 用于设计能量管理策略 10 蓄电池组最大充电电流/A -100 -1.5 用于设计能量管理策略 11 蓄电池容量/(kW·h) 1 806 10 减少试验时间
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表 6 氢气消耗量以及SOC末端值
Table 6. Hydrogen consumption and final SOC values
策略 工况 平均瞬时效率/% 直接氢气消耗量/g SOC末端值/ % 间接等效氢气消耗量/g 总等效氢气消耗量/g 既有策略Ⅰ 稳态 50.27 7 316.80 33.11 3 214.83 10 531.63 瞬态 49.50 3 654.48 49.82 1 530.30 5 184.78 既有策略Ⅱ 稳态 53.08 7 072.91 33.11 3 214.83 10 287.74 瞬态 51.44 3 583.05 49.82 1 530.30 5 113.35 状态机策略 稳态 53.43 8 857.88 51.36 1 375.05 10 232.93 瞬态 52.49 4 096.06 57.92 713.74 4 809.80
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表 7 混合动力系统统计量
Table 7. Statistical metrics of hybrid power systems
策略类型 工况 母线电压标准差/V 功率标准差/W 策略模式切换频次 燃料电池启用数量变化频次 燃料电池 蓄电池 既有策略Ⅰ 稳态 0.69 330.81 85.62 96 0 瞬态 0.76 219.65 110.85 132 0 既有策略Ⅱ 稳态 0.69 330.81 85.62 96 743 瞬态 0.76 219.65 110.85 132 218 状态机策略 稳态 1.24 225.32 169.58 125 126 瞬态 0.72 144.37 104.37 30 20
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