Investigation on Energy Flow Characteristics of Fuel Cell System Based on Real Vehicle Tests

For fuel cell hybrid vehicles, the energy distribution mechanism of the fuel cell and power battery should reasonably allocate the power output of the fuel cell and power battery, optimize the efficiency of both and control the power battery SOC to fluctuate within a reasonable range. To test the energy flow and operation characteristics of the powertrain of two hybrid car models on the market, two test vehicles (called vehicle A and vehicle B in this paper) are tested on an AIP 4WD chassis dynamometer under constant power and the China Light-Duty Vehicle Test Cycle-Passenger cycle condition, respectively. The test results show that vehicle A has a smaller power battery SOC variation interval and a lower variable rate than vehicle B. The cumulative power battery output energy of vehicle B is more significant than that of vehicle A. More importantly, the current rare public test reports of fuel cell vehicles make this study very valuable. This paper has important reference significance for the energy flow characteristics and energy management strategy of existing fuel cell hybrid vehicles.

Estimation of Real-World Fuel Consumption Rate of Light-Duty Vehicles Based on the Records Reported by Vehicle Owners

Private vehicle travel is the most basic mode of transportation, so that an effective way to control the real-world fuel consumption rate of light-duty vehicles plays a vital role in promoting sustainable economic growth as well as achieving a green low-carbon society. Therefore, the factors impacting individual carbon emissions must be elucidated. This study builds five different models to estimate the real-world fuel consumption rate of light-duty vehicles in China. The results reveal that the light gradient boosting machine (LightGBM) model performs better than the linear regression, naïve Bayes regression, neural network regression, and decision tree regression models, with a mean absolute error of 0.911 L/100 km, a mean absolute percentage error of 10.4%, a mean square error of 1.536, and an R-squared (R2) value of 0.642. This study also assesses a large pool of potential factors affecting real-world fuel consumption, from which the three most important factors are extracted, namely, reference fuel-consumption-rate value, engine power, and light-duty vehicle brand. Furthermore, a comparative analysis reveals that the vehicle factors with the greatest impact are the vehicle brand, engine power, and engine displacement. The average air pressure, average temperature, and sunshine time are the three most important climate factors.

Effect of tire slip losses on the energy demand and fuel consumption of a light-duty vehicle

The contribution of the tire-road slip of traction wheels to the total resistance opposing the motion of a light-duty commercial vehicle has been investigated through the simulation of several homologation and custom driving cycles. The calculation of the contribution of the tire slip losses was based on the estimation of the longitudinal tire slip, by means of Pacejka’s MF5.2 tire model. In this work, the computational steps required to evaluate this contribution were implemented in a previously developed fuel consumption simulation tool. Simulations were performed under several vehicle loading conditions and tire inflation pressures on traction and non-traction wheels, and considering different tire-road adherence conditions, in order to obtain a characterization of the tire slip losses over a wide range of working conditions. An analysis of the results shows that, although the contribution of tire slip losses to the total vehicle energy demand and fuel consumption may be relevant – especially under low-load, low adherence conditions – the sensitivity of the average on-cycle vehicle energy/fuel consumption to changes in the tire inflation pressure is only affected slightly by tire slip losses. Therefore, tire slip losses can be neglected in practice, when the aim of a simulation is to optimize the tire pressure to achieve average vehicle working conditions over a driving cycle.