Refine Your Search

Topic

Author

Affiliation

Search Results

Technical Paper

Predictive Energy Management for Dual Motor-Driven Electric Vehicles

2022-02-14
2022-01-7006
Developing pure electric powertrains have become an important way to reduce reliance on crude oil in recent years. This paper concerns energy management of dual motor-driven electric vehicles. In order to obtain a predictive energy management strategy with good performance in computation and energy efficiency, we propose a hybrid algorithm that combines model predictive control (MPC) and convex programming to minimize electrical energy use in real time control. First, few changes are occurred in original component models in order to convert the original optimal control problem into convex programming problem. Then convex optimization algorithm is used in the prediction horizon to optimize torque allocation between two electric motors with different size. To verify the effectiveness of the hybrid algorithm, a real city driving cycle is simulated. Furthermore, different predictive horizons are performed to illustrate the robustness and time efficiency of the proposed method.
Technical Paper

Vehicle Energy Dissipation during Curb Traversal

2022-01-04
2022-01-5002
Previously published vehicle curb traversal test data for 122 full-scale vehicle tests were examined to evaluate the change in a vehicle’s kinetic energy during traversal of a roadside curb while rolling on its wheels. This change in energy was correlated to test parameters including the ratio of tire radius to curb height, vehicle approach angle, and vehicle speed at curb contact. Various regression relationships quantifying the change in vehicle kinetic energy during curb traversal versus the above parameters were examined, wherein the kinetic energy change was expressed as an equivalent energy speed (EES) in which the energy change was normalized using the test vehicle’s mass. No statistical significance was observed in relations involving EES as a function of parameters which included approach angle and the ratio of tire radius to curb height.
Technical Paper

Improving Combustion Performance of a Dedicated Range-Extender Engine with Refined Intake-Charging Characteristics and Cooled EGR

2021-12-31
2021-01-7001
Studies were carried out for improvement of combustion performance of an 1.2 L dedicated range-extender gasoline engine which uses a high compression ratio, cooled exhaust-gas-recirculation (EGR) and Atkinson cycle. The intake-charging characteristics were investigated both computationally and experimentally in order to compensate the torque reduction mainly due to the charge pushback in the Atkinson cycle. The design parameters of the intake manifold were refined to increase the intake air charges. 1D simulations were carried out to investigate the effect of the runner lengths and diameters. The results indicated that the increased length and reduced diameter could improve the volumetric efficiency in the most used engine speed range. Furthermore, computational fluid dynamics (CFD) simulations were employed to evaluate the cylinder-to-cylinder charging variations of the proposed manifold and reduced variations were obtained.
Technical Paper

Traffic Flow Velocity Prediction Based on Real Data LSTM Model

2021-12-31
2021-01-7014
In order to improve the energy efficiency of hybrid electric vehicles and to improve the effectiveness of energy management algorithms, it is very important to predict the future changes of traffic parameters based on traffic big data, so as to predict the future vehicle speed change and to reduce the friction brake. Under the framework of deep learning, this paper establishes a Long Short-Term Memory (LSTM) artificial neural network traffic flow parameter prediction model based on time series through keras library to predict the future state of traffic flow. The comparison experiment between Long Short-Term Memory (LSTM) artificial neural network model and Gate Recurrent Unit (GRU) model using US-101 data set shows that LSTM has higher accuracy in predicting traffic flow velocity.
Technical Paper

Tooth Profile Modification Analysis of Fine-Pitch Planetary Gears for High-Speed Electric Drive Axles Based on KISSsoft

2021-12-31
2021-01-7016
According to the requirements of high transmission ratio and high load torque of high-speed electric drive axle planetary gear system, the design and analysis of fine-pitch planetary gear system with small modulus, small pressure angle and high full tooth height of are carried out. In order to improve the bearing capacity of gear and reduce gear meshing noise, the tooth profile modification parameters of gear system are optimized. In this paper, the tooth modification methods are analyzed and the gear train parameters are determined. The influence degree of different tooth modification methods on the transmission performance of the gear train is determined by orthogonal experiment method. The transmission error is reduced, the stress fluctuation is improved, and the gear meshing performance is greatly improved by adopting the appropriate modification scheme, which proves the effectiveness of the tooth modification scheme.
Technical Paper

A Comparative Study on Energy Management Strategies for an Automotive Range-Extender Electric Powertrain

2021-12-31
2021-01-7027
In this work, the influences of various real-timely available energy management strategies on vehicle fuel consumption (VFC) and energy flow of a range-extender electric vehicle were studied The strategies include single-point, multi-point, speed-following, and equivalent consumption minimization strategy. In addition, the dynamic programming method which cannot be used in real time, but can provide the optimal solution for a known drive situation was used for comparison. VFCs and energy flow characteristics with different strategies under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) were obtained through computer modeling, and the results were verified experimentally on a range-extender test bench. The experimental results are consistent with the modeled ones in general with a maximum deviation of 4.11%, which verifies the accuracy of the simulation models.
Technical Paper

Hybrid Electric Vehicle Energy Management Based on Network Technology

2021-12-31
2021-01-7036
HEV energy management strategy acquired a lot of attention due to the rapid growth of New Energy Vehicle (NEV) and Intelligent and Connected Vehicles (ICV). In this study, the vehicle was modelled in GT-suit and simulated with dynamic programming (DP) strategy, the result shows that the relationship between the state of charge (SOC) curve and the driving distance was approximately linear. Then a simplified network-based piece-wise linear equivalent fuel consumption minimization strategy (PLF-ECMS) is designed and applied to the HEV in road test. Finally, the experimental result shows that based on the trajectory and traffic information, the fuel consumption potential of PWL-ECMS was outstanding. The test result of vehicle fuel consumption with network information can be 37.8% lower than without network information when E-Drive remaining distance around 65% of total driving distance.
Technical Paper

Analysis of Hybrid Electric Transmission with Over Ten Speed Ratios

2021-12-31
2021-01-7037
A hybrid transmission with more than 10 times speed ratio is introduced in this paper. The transmission consists of a electric torque converter module (eTC) and a dual input-shaft gearbox (DIG). The configuration structure and operation mode of the hybrid system based on eTC-DIG are analyzed in detail. The hybrid module comprises a motor, a planetary gear set (PGS), and a clutch. The rotating elements of the PGS are connected to engine shaft, motor shaft, and two input shafts of DIG, respectively, in such a way, that a new speed ratio is created between each odd-numbered gearset and an adjacent even-numbered gearset. The transmission has twice as many speed ratios for the engine as the number of the speed-changing gear sets. The hybrid system can realize a variety of working modes and eliminate the dual clutch of DCT, which greatly reduces the cost and risk. The economic simulation of the hybrid system is carried out for a Pickup truck.
Technical Paper

Design and Simulation of Hairpin Winding Motors

2021-12-31
2021-01-7039
This work aims to design two different layers of hairpin winding and simulate the loss of the hairpin winding. With the rise of pure electric and hybrid electric vehicle, hairpin winding motor has been developed and applied rapidly. Because of the high speed of motor, the eddy loss of hairpin winding is especially obvious, which affects the efficiency and temperature rise of motors. In this paper, the basic principle of eddy loss is introduced, and two different layers winding with 4-layer and 8-layer are designed. Through the simulation analysis, it was found that the winding loss of 4-layer winding motor is much larger, and the loss difference between layers is very big. Finally, the 8-layer winding motor scheme is chosen. Therefore, the winding loss of more layers winding decreases at higher speed, but increases at lower speed, and the process cost increases with the number of layers. So the selection of several layers requires simulation,comparison, and comprehensive consideration.
Technical Paper

Optimization of Electric Powertrain for Auto-rickshaw

2021-12-23
2021-01-5111
With the need for a compact system of transportation, the auto-rickshaw has evolved over the years, and since then auto-rickshaws have proven to be an important means of public transport. Lately, auto-rickshaws have been contributing enormously to air pollution. Due to this, people are preferring alternative means of transportation, and electrification is one of them. Electrification of auto-rickshaws results in a low-cost and environment-friendly source of transportation in urban cities where pollution rates are alarmingly high. The efficiency of electric auto-rickshaws plays a significant role because it has to compete with the present internal combustion (IC) engine auto-rickshaws and should have a higher priority to be chosen as the public’s option of transport. The primary aim of this project is to optimize the electric powertrain for auto-rickshaws by minimizing the consumption of energy.
Technical Paper

Machine-Learned Emission Model for Diesel Exhaust On-Board Diagnostics and Data Flow Processor as Enabler

2021-12-17
2021-01-5108
Conventional methods of physicochemical models require various experts and a high measurement demand to achieve the required model accuracy. With an additional request for faster development time for diagnostic algorithms, this method has reached the limits of economic feasibility. Machine learning algorithms are getting more popular in order to achieve a high model accuracy with an appropriate economical effort and allow to describe complex problems using statistical methods. An important point is the independence from other modelled variables and the exclusive use of sensor data and actuator settings. The concept has already been successfully proven in the field of modelling for exhaust gas aftertreatment sensors. An engine-out nitrogen oxide (NOX) emission sensor model based on polynomial regression was developed, trained, and transferred onto a conventional automotive electronic control unit (ECU) and also proves real-time capability.
Technical Paper

Research on Automatic Lane Change Path Planning Based on Improved Rapidly-Exploring Random Trees

2021-12-15
2021-01-7018
In order to solve the problem of automatic lane change in straight road environment, a Segment-orienting rapidly-exploring random trees algorithm (SO-RRT) is designed based on the idea of Fast-biasing RRT algorithm and piecewise design. Firstly, the local map is preprocessed, and then the control points are obtained by geometric analysis of the map according to the obstacle vehicle around the vehicle and the speed of the vehicle. On this basis, the Fast-bias RRT is carried out in segments, and the obtained path is optimized and fitted. After processing, the planned path is finally obtained, which ensures that the planned path meets the kinematic constraints of the vehicle and is as close as possible to the optimal solution. CarSim was used for vehicle and road modeling and co-simulation with Matlab / Simulink. The path planning was carried out in Simulink and the hybrid algorithm combining model predictive control algorithm and PID algorithm was used to realize path tracking.
Technical Paper

Research on SLAM Based on the Fusion of Stereo Vision and Inertial Measurement Unit

2021-12-15
2021-01-7017
With the continuous improvement of positioning technology and industry demand, the shortcomings of each sensor are constantly amplified. Only relying on a single sensor, the demand of high-precision positioning and mapping for intelligent vehicles is difficult to be satisfied. The accuracy of system positioning and mapping is reduced due to the loss of feature points in pure visual SLAM as the environmental characteristics are not obvious or the texture is not abundant. IMU is a sensor with low cost and high update frequency, which can correct the running trajectory in real time and reduce the error of environmental factors on visual sensor data. Therefore, a method based on ORB_SLAM2 algorithm and VINS-Fusion algorithm, the stereo camera information and inertial measurement unit information are extracted and fused in robot operating system is proposed.
Technical Paper

Automatic Emergency Collision Avoidance of Four-Wheel Steering Based on Model Following Control

2021-12-15
2021-01-7015
In order to improve the performance of automatic emergency steering and collision avoidance of intelligent vehicle, two automatic steering control methods under ideal model following control are proposed. The two ideal reference models are the reference model with zero sideslip angle of vehicle gravity center and the reference model with no phase-lag in vehicle lateral acceleration. The control system adopts the combination of outer loop and inner loop. In the design of the outer loop controller, the optimal control is used to get the steering wheel angle needed to avoid collision. The inner loop controller uses feedforward and feedback control to get the required front and rear wheel steering angles. Taking vehicle two degrees of freedom (DOF) lateral dynamics model as the research object, the vehicle collision avoidance reference trajectory is obtained through the fifth-degree polynomial.
Technical Paper

Path Tracking for Driverless Vehicle Under Parallel Parking Based on Model Predictive Control

2021-12-15
2021-01-7011
In order to solve the problems of accuracy, comfort and robustness of driverless vehicles under parallel parking condition, a control method of path tracking based on model predictive control (MPC) is studied. The kinematics model of driverless vehicle under parking condition is established. The calculation method of minimum parking space size required for parking is proposed. The linear error model of vehicle kinematics is established. In order to make the vehicle track the desired path quickly and smoothly, an appropriate objective function is designed. In rolling optimization, the constraint conditions of velocity and front wheel steering angle are imposed on the objective function to achieve the solution in the control period, the control input constraint and control increment constraint are set. In order to ensure the stability of the path tracking process, constraint condition of velocity is set.
Technical Paper

Lane-Change Planning with Dynamic Programming and Closed-Loop Forward Simulation for Autonomous Vehicle

2021-12-15
2021-01-7012
This paper proposed a lane-change planning method for autonomous vehicle, aiming at fast obstacles avoidance in a way that make smooth and comfortable. The panning algorithm consists of dynamic programming and closed-loop forward simulation. The dynamic programming (DP) was employed to fast search a reference trajectory that avoids obstacles in topological configure space. And the closed-loop forward simulation (CFS) was used to track the reference trajectory for generating smooth trajectory, since the CFS being able to incorporate any nonlinear law and nonlinear vehicle constraints. Furthermore, an anti-windup lateral controller was designed to make the closed-loop forward simulation robust, as the controller being proved to be stable by Lyapunov function. Finally, the numerical results are provided to illustrate the effectiveness of the proposed method.
Technical Paper

Automatic Calibration for Road Side Lidar and Camera Using Planar Target

2021-12-15
2021-01-7023
In recent years, vehicle-intelligent road cooperation is gaining an increasing attention from both academia and industry, which require deployment of a large scale of road side sensors such as lidar and camera. For the road side sensors, calibration is indispensable to obtain transformation between sensor coordinate frame and geographic coordinate frame. Currently, manual measuring using RTK and marking correspondent feature points in sensors’ field of view is the commonly used method of calibration, which is far too complicated. To simplify the calibration task and improve efficiency, an automatic calibration method for road side lidar and camera using a planar calibration target is proposed in this paper. The feature of planar target is designed to be easily identified by the sensors, and an Integrated Navigation System (INS), which acquires the geographic coordinate of itself in real time at an accuracy of centimeter level, is fixed on the target.
Technical Paper

Recognition of Surrounding Vehicles Driving Behavior Based on Gaussian Mixture Model-Hidden Markov Model for Autonomous Vehicle

2021-12-15
2021-01-7020
Vehicle driving behavior recognition is critical to improve the safety and rationality of autonomous vehicle decision-making and planning in heterogeneous vehicle mixed scenarios. Aiming at the problems that traditional driving behavior recognition methods only consider a single driving behavior, which has insufficient recognition accuracy, and the lack of consideration of the impact on the neighborhood between traffic subjects, the algorithm robustness is poor. A driving behavior recognition method based on Gaussian mixture hidden Markov model (GMM-HMM) is proposed. Firstly, preprocess the NGSIM data sample, take the surrounding vehicles lateral displacement, lateral speed are taken as the HMM observation sequence, the HMM driving behavior recognition model is established. Then, the Baum-Welch algorithm and the Viterbi algorithm are used to train the parameters of the HMM to obtain Hidden state sequence of driving behavior.
Technical Paper

Lane Marking Detection for Highway Scenes based on Solid-state LiDARs

2021-12-15
2021-01-7008
Lane marking detection plays a crucial role in Autonomous Driving Systems or Advanced Driving Assistance System. Vision based lane marking detection technology has been well discussed and put into practical application. LiDAR is more stable for challenging environment compared to cameras, and with the development of LiDAR technology, price and lifetime are no longer an issue. We propose a lane marking detection algorithm based on solid-state LiDARs. First a series of data pre-processing operations were done for the solid-state LiDARs with small field of view, and the needed ground points are extracted by the RANSAC method. Then, based on the OTSU method, we propose an approach for extracting lane marking points using intensity information.
Technical Paper

Online Capacity Estimation of Lithium-ion Battery Based on Incremental Capacity Analysis with Interpretable Features

2021-12-15
2021-01-7009
Accurate and online capacity estimation is of extreme importance to maintain the continuous operation of lithium-ion batteries. This paper proposes an indirect capacity estimation method based on the incremental capacity features and model interpretability. First, the current and voltage data of the battery are collected in real-time to construct the incremental capacity curves. The dual filter, which consists of a moving average and a Gaussian filter, is then used to smooth the curves. To achieve satisfying filtering effects, the filter window size and calculation frequency are determined by comparing different sets of conditions. 15 multiple alternative features related to the curve peak position and area are extracted. The Shapley value method based on cooperative game theory is introduced to reduce the dimension of the feature vector and to determine the key features.
X