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Technical Paper

Research on Trajectory Planning and Tracking Strategy of Lane-changing and Overtaking based on PI-MPC Dual Controllers

2021-10-11
2021-01-1262
Aiming at the problem of poor robustness after the combination of lateral kinematics control and lateral dynamics control when an autonomous vehicle decelerates and changes lanes to overtake at a certain distance. This paper proposes a trajectory determination and tracking control method based on a PI-MPC dual algorithm controller. To describe the longitudinal deceleration that satisfies the lateral acceleration limit during a certain distance of lane change, firstly, a fifth-order polynomial and a uniform deceleration motion formula are established to express the lateral and longitudinal displacements, and a model prediction controller (MPC) is used to output the front wheel rotation angle. Through the dynamic formula and the speed proportional-integral (PI) controller to control and adjust the brake pressure.
Technical Paper

Surface Functional Groups and Graphitization Degree of Soot in the Sooting History of Methane Premixed Flame

2017-03-28
2017-01-1003
The evolution of surface functional groups (SFGs) and the graphitization degree of soot generated in premixed methane flames are studied and the correlation between them is discussed. Test soot samples were obtained from an optimized thermophoretic sampling system and probe sampling system. The SFGs of soot were determined by Fourier transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS) after removing the soluble impurities from the soot samples, while the graphitization degree of soot was characterized by Raman spectrum and electron energy loss spectroscopy (EELS). The results reveal that the number of aliphatic C-H groups and C=O groups shows an initial increase and then decrease in the sooting history. The large amount of aliphatic C-H groups and small amount of aromatic C-H groups in the early stage of the soot mass growth process indicate that aliphatic C-H groups make a major contribution to the early stage of soot mass growth.
Technical Paper

Multiple Engine Faults Detection Using Variational Mode Decomposition and GA-K-means

2022-03-29
2022-01-0616
As a critical power source, the diesel engine is widely used in various situations. Diesel engine failure may lead to serious property losses and even accidents. Fault detection can improve the safety of diesel engines and reduce economic loss. Surface vibration signal is often used in non-disassembly fault diagnosis because of its convenient measurement and stability. This paper proposed a novel method for engine fault detection based on vibration signals using variational mode decomposition (VMD), K-means, and genetic algorithm. The mode number of VMD dramatically affects the accuracy of extracting signal components. Therefore, a method based on spectral energy distribution is proposed to determine the parameter, and the quadratic penalty term is optimized according to SNR. The results show that the optimized VMD can adaptively extract the vibration signal components of the diesel engine. In the actual fault diagnosis case, it is difficult to obtain the data with labels.
Technical Paper

Experimental Study on Combustion Characteristics of Methane/Gasoline Dual-Fuel in a SI Engine at Different Load Conditions

2018-04-03
2018-01-1140
Methane as an attractive alternative fuel offers the most potential in clean combustion and low CO2 emissions. In this work, combustion characteristics of methane/gasoline dual-fuel were investigated in a spark-ignited engine with port-injection of methane and direct-injection of gasoline, allowing for variations in methane addition and excess air coefficient. Engine experimental results showed that under low load conditions, as methane mass rate was raised, there was a promotion in methane/gasoline dual-fuel combustion, and this became more obvious at lean conditions. Similar observations were also obtained when the engine was operated at intermediate load conditions, but a prolonged combustion duration was found with the methane addition. Further analysis showed that the promotion of methane/gasoline dual-fuel combustion with methane addition mainly occurred in the early stage of combustion, especially for lean conditions.
Technical Paper

A Rule-Based Energy Management Strategy for a Light-Duty Commercial P2 Hybrid Electric Vehicle Optimized by Dynamic Programming

2021-04-06
2021-01-0722
An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy.
Technical Paper

Deep Optimization of Catalyst Layer Composition via Data-Driven Machine Learning Approach

2020-04-14
2020-01-0859
Proton exchange membrane fuel cell (PEMFC) provides a promising future low carbon automotive powertrain solution. The catalyst layer (CL) is its core component which directly influences the output performance. PEMFC performance can be greatly improved by the effective optimization of CL composition. This work demonstrates a deep optimization of CL composition for improving the PEMFC performance, including the platinum (Pt) loading, Pt percentage of carbon-supported Pt and ionomer to carbon ratio of the anode and the cathode,. The simulation results by a PEMFC three-dimensional (3D) computation fluid dynamics (CFD) model coupled with the CL agglomerate model is used to train the artificial neural network (ANN) which can efficiently predict the current density under different CL composition. Squared correlation coefficient (R-square) and mean percentage error in the training set and validation set are 0.9867, 0.2635% and 0.9543, 1.1275%, respectively.
Journal Article

Laminar Burning, Combustion and Emission Characteristics of Premixed Methane- Dissociated Methanol-Air Mixtures

2017-03-28
2017-01-1289
This research presents an experimental study of the laminar burning combustion and emission characteristics of premixed methane -dissociated methanol-air mixtures in a constant volume combustion chamber. All experiments were conducted at 3 bar initial pressure and 373K initial temperature. The dissociated methanol fractions were from 20% to 80% with 20% intervals, and the equivalence ratio varied from 0.6 to 1.8 with 0.2 intervals. The images of flame propagation were visualized by using a schlieren system. The combustion pressure data were measured and exhaust emissions were sampled with a portable exhaust gas analyzer. The results show that the unstretched laminar burning velocities increased significantly with dissociated methanol enrichment. The Markstein length decreased with increasing dissociated methanol fraction and decreasing equivalence ratio.
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