Aerodynamic Performance Optimization of Vehicle-Mounted Photovoltaic System for Net Power Maximization

doi:10.12141/j.issn.1000-565X.250070

Abstract

Abstract:

The present researches on vehicle-mounted photovoltaic systems mainly focus on increasing the installation area of photovoltaic panels by optimizing the folding mechanism to enhance the power generation capacity, while neglecting the issue of the synergistic optimization of power generation capacity and the additional drag energy consumption of the system. To enhance the net power of vehicle-mounted photovoltaic systems, by optimizing the aerodynamic performance of the system, this paper presents a new methodology to reduce the additional drag energy consumption imposed by the system on the vehicle, and thereby to increase the net power of the system. Firstly, a foldable vehicle-mounted photovoltaic system was designated as the object, and a high-transmittance fairing and a tail wing that conform to the aerodynamic principle were designed. Subsequently, three design variables, namely the front tilt angle of the fairing, the back angle, and the system height, were selected to optimize the shape of the fairing. Through the construction of an orthogonal test scheme and the analysis of polar deviation, the influence degree of the three design variables on the system aerodynamic drag was obtained as system height > front tilt angle > back angle. From the analysis of the main effect plot, the three variables are found exhibiting monotonic effects on the aerodynamic drag of the system, thus determining the structural parameters of the fairing shape as follows: a front tilt angle of 70°, a back angle of 0°, and a system height of 100mm. Subsequently, the tail attack angle of the vehicle-mounted photovoltaic system was optimized, a cubic spline interpolation approximation model was constructed based on the experimental data, and the tail attack angle with optimal lift-to-drag ratio was obtained as 33.96°. In addition, the vehicles equipped with the on-board photovoltaic system proposed in this paper were compared with those without the system. It is found that the air resistance coefficient decreases by 44.59%, the aerodynamic resistance decreases by 22.45% and the lift coefficient decreases by 226.15%, and that the direction of the lift undergoes a transformation from upward to downward. This transformation serves to mitigate the adverse impact of upward aerodynamic lift on the handling and safety performance of the entire vehicle. A comparison of the original vehicle model with the modified version reveals a significant decrease of air resistance coefficient of 17.35% and a modest aerodynamic resistance increase of 3.14 N, which means that the modification effectively mitigates the adverse effects of the on-board photovoltaic system on vehicle’s aerodynamic performance. Finally, a comparison and analysis of the net power of the on-board photovoltaic system before and after the optimization was conducted. It is found that the proposed optimization scheme can effectively increase the net power generation of the vehicle-mounted photovoltaic system during vehicle operation. When the vehicle speed is 40.0 m/s, the net power difference reaches 7 723.62 W.

Key words: vehicle-mounted photovoltaic system, aerodynamic performance optimization, net power

CLC Number:

U463.99

LUO Yutao, LIN Zhiqiang. Aerodynamic Performance Optimization of Vehicle-Mounted Photovoltaic System for Net Power Maximization[J]. Journal of South China University of Technology(Natural Science Edition), 2025, 53(11): 122-131.

Figures/Tables 27

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Table 1

Table 2

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

Fig.11

Table 3

Table 4

Fig.12

Fig.13

Fig.14

Fig.15

Fig.16

Table 5

Fig.17

Table 6

Table 7

Fig.18

Table 8

Table 9

References 18

[1]	林泽权，赵斌，裴刚．基于典型气象数据的太阳能汽车年性能分析［J］．太阳能学报，2024，45（7）：577-583．
	LIN Zequan， ZHAO Bin， PEI Gang ．Annual performance analysis of solar vehicle based on typical meteorological data［J］．Acta Energiae Solaris Sinica，2024，45（7）：577-583．
[2]	孟宝．汽车可折叠式太阳能板追光系统的设计与研究［D］．长春：吉林大学，2017．
[3]	王鑫恫．具有自动追光功能的太阳能电动汽车能量管理系统研究［D］．淄博：山东理工大学，2021．
[4]	赵轩．房车光伏电池板折叠机构自动追光系统设计与研究［D］．西安：西安理工大学，2021．
[5]	ARAKI K， JI L， KELLY G，et al ．To do list for research and development and international standardization to achieve the goal of running a majority of electric vehicles on solar energy［J］．Coatings，2018，8（7）：251．
[6]	谷正气．汽车空气动力学［M］．北京：人民交通出版社，2005．
[7]	曾勇，张光亚，黄炎．一种车载太阳能充电系统的原理与应用研究［J］．时代汽车，2023（15）：114-116．
	ZENG Yong， ZHANG Guangya， HUNG Yan ．Research on the principle and application of a vehicle solar charging system［J］．Auto Time，2023（15）：114-116．
[8]	ROLLET-MIET P， LAURENCE D， FERZIGER J ．LES and RANS of turbulent flow in tube bundles［J］．Internation Journal of Heat and Fluid Flow，1999，20（3）：241-254．
[9]	张群峰，何洪涛．不同湍流模型数值模拟三维轴对称凸体分离流动的比较［J］．科学技术与工程，2010，28（2）：3693‐3703．
	ZHANG Qun-feng， HE Hong-tao ．Numerical study on three-dimensional separated flow on an axisymmetric bump by different turbulent models［J］．Science Technology and Engineering，2010，28（2）：3693‐3703．
[10]	王坤阳．车顶箱对整车气动减阻的影响研究［D］．长春：吉林大学，2019．
[11]	谷正气，王师，仇健，等．MIRA模型组尾部造型风洞试验研究［J］．科技导报，2011，2908：67-71．
	GU Zhengqi， WANG Shi， QIU Jian，et al ．Wind tunnel tests of MIRA model group for study of vehicle’s rear shape［J］．Science & Technology Review，2011，29（8）：67-71．
[12]	贾浩．某车型行李架气动噪声与阻力的协同优化及分析［D］．重庆：重庆理工大学，2021．
[13]	廉玉波，罗秋丽，张风利，等．基于形体优化方法的汽车空气动力学开发［J］．汽车工程，2022，44（10）：1619-1626．
	LIAN Yubo， LUO Qiuli， ZHANG Fengli，et al ．Automotive aerodynamics development based on shape optimization method［J］．Automotive Engineering，2022，44（10）：1619-1626．
[14]	张喆，宋世达，王国华，等．赛车俯仰运动下的气动特性［J］．吉林大学学报（工学版），2023，53（8）：2201-2211．
	ZHANG Zhe， SONG Shi-da， WANG Guo-hua，et al ．Aerodynamic characteristics of a racing car in pitching motion［J］．Journal of Jilin University （Engineering and Technology Edition），2023，53（8）：2201-2211．
[15]	MIRZA A F， MANSOOR M， LING Q ．A novel MPPT technique based on Henry gas solubility optimization［J］．Energy Conversion and Management，2020，225：113409/1-22．
[16]	ZUO K， YE Z， ZHANG W，et al ．Fast aerodynamics prediction of laminar airfoils based on deep attention network［J］．Physics of Fluids，2023，35（3）：037127．
[17]	WU H， LIU L， AN W，et al ．A generative deep learning framework for airfoil flow field prediction with sparse data［J］．Chinese Journal of Aeronautics，2022，35（1）：470-484．
[18]	PATEL N， BITTKAU K， PIETERS B E，et al ．Impact of additional PV weight on the energy consumption of electric vehicles with onboard PV［J］．IEEE Journal of Photovoltaics，2024，14（2）：319-329．

编号	加密网格尺寸/mm				体网格数/10⁶	C_d	C₁
编号	1层	2层	3层	4层	体网格数/10⁶	C_d	C₁
1	15	52	200	300	5.12	0.432	-0.010 0
2	10	52	200	300	8.71	0.415	-0.008 1
3	8	52	200	300	15.38	0.411	-0.008 0
4	6	30	150	300	36.63	0.412	-0.008 2

车辆类别	C_d	F_D/N	C₁	F_C/N
原型车	0.415	372.42	-0.008	-7.22
安装后	0.619	484.26	0.065	57.61

参数	取值上限	取值下限	水平数
前倾角/（°）	70	10	4
后背角/（°）	60	0	3
系统高度/mm	200	100	3

编号	前倾角/（°）	后背角/（°）	系统高度/mm	C_d	F_D/N	C_l	F_C/N
1	10	0	100	0.62	44.15	1.07	78.66
2	10	30	150	0.63	48.85	1.09	79.00
3	10	60	200	0.65	53.66	1.19	85.91
4	30	0	150	0.58	45.27	0.99	76.75
5	30	30	200	0.64	53.17	1.08	78.82
6	30	60	100	0.60	43.04	1.19	85.55
7	50	0	200	0.60	47.39	1.02	77.24
8	50	30	100	0.56	39.83	1.10	78.98
9	50	60	150	0.58	45.05	1.18	85.25
10	70	0	100	0.46	33.30	0.98	74.61
11	70	30	150	0.47	37.19	1.09	79.02
12	70	60	200	0.53	49.07	1.10	80.62
k₁	48.89	42.53	40.08
k₂	47.16	44.76	44.09
k₃	44.09	47.70	50.82
k₄	39.85
极差	9.04	5.17	10.74
最优方案	70	0	100

尾翼角度/（°）	C_d	C₁		C_d	C₁
40	0.343	-0.066	-10	0.360	0.049
30	0.347	-0.074	-20	0.358	0.048
20	0.360	0.017	-30	0.356	0.053
10	0.360	0.018	-40	0.357	0.066
0	0.356	0.050