Research of two speed DCT electric power-train and control system

University of Technology Sydney. Faculty of Engineering and Information Technology.The research for this thesis is based on an international cooperation project with BAIC Motor Electric Vehicle Co. Ltd, UTS and AVL/NTC. It aims to develop a sample of a two speed DCT used in an electric drive system. For the dual clutch’s structural characteristics, one clutch is connected with one gear, so it is very simple to realize two speed driving. Simulation models are built in a co-simulation platform using AMESim and Simulink. Gear ratio selection is processed during the matching of Q60FB and C70GB vehicles. The ratios selected are 2nd and 3rd gear, and the ratios are 8.45 and 5.36. The prototype is modified from a VW 6spd DCT to operate at 2 speeds. The work primarily involves modification of the mechanical part of the gears and shaft, and changing the hydraulic parts. To optimize vehicle dynamics and economic performance, a shifting schedule calculation method for PEVs is provided. This uses a graphical development method and is adapted for the purposes of simulations and experimental work. As long as gear shifts are initiated according to the schedule, the EM will be maintained at a higher efficiency operating region. As a result, the proposed method provides more efficient operations of the PEV. Study of the control algorithm, including the vehicle control algorithm and shift control algorithm, is the core of this thesis. To investigate shift control and its calibration of a two speed DCT electric drive power-train, this thesis analyzes the shifting process. The vehicle control algorithm section follows the judgment of the pure electric multimode algorithm. The shift control section analyses the traditional DCT control shifting algorithm. In addition, the shifting control algorithm is based on motor active braking control. Detailed shifting control algorithms are developed which include power-on and power-off methods. Corresponding simulation analysis has also been carried out. The rig test uses the UTS power-train test bench for the purposes of modification. Calibration and testing works are employed for processing and the test rig mainly calibrates the shift control algorithm, DCT temperature testing, and NEDC and UDDS drive cycles testing. Vehicle integration and testing are finished at BJEV. This is based on the BAIC independent brand car of Q60FB, with two gear DCT prototype mounting and road test calibration. Finally, the project tests dynamic and economic performance

고성능 한계 핸들링을 위한 인휠모터 토크벡터링 제어

학위논문(박사) -- 서울대학교대학원 : 공과대학 기계항공공학부, 2021.8. 이경수.지난 10년 동안 차량 자세 제어시스템(ESC)은 치명적인 충돌을 방지하기 위해 많은 상용 차량에서 비약적으로 발전되고 개발되고 있다. 특히, 차량 자세 제어 시스템은 악천후로 인한 미끄러운 도로와 같은 위험한 도로에서 불안정한 차량 주행 조건에서 사고를 피하는데 큰 역할을 한다. 그러나, 최근의 경우, 고성능 차량 또는 스포츠카 등의 경우 제동제어의 빈번한 개입은 운전의 즐거움을 감소시키는 불만도 존재한다. 최근 차량의 전동화와 함께, 자량 자세 제어시스템의 작동 영역인 한계 주행 핸들링 조건에서 각 휠의 독립적인 구동을 적용 할 수 있는 시스템 중 하나인 인휠 모터 시스템을 사용하여 차량의 종, 횡방향 특성을 제어 가능하게 하는 토크 벡터링 제어기술에 대한 연구가 활발하다. 따라서, 본 연구에서는 차량의 선회 한계 핸들링 조건에서 안정성과 주행 다이나믹 성능을 향상시킬 수 있는 토크 벡터링 제어기를 제안하고자 한다. 먼저, 차량의 비선형 주행 구간인 한계 핸들링 조건에 대한 자동 드리프트 제어 알고리즘을 제안한다. 이 알고리즘을 이용하여 토크벡터링제어에 차량의 다이나믹한 주행모드에 대한 통찰력을 제공하고 미끄러운 도로에서 차량의 높은 슬립 각도의 안정성 제어를 제공 할 수 있다. 또한, 인휠 모터 시스템을 차량의 전륜에 2개 모터로 사용하여 차량 고유의 특성인 차량 언더스티어 구배를 직접적 제어를 수행하여, 차량의 핸들링 성능을 향상시켰다. 제어기의 채터링 효과를 줄이고 빠른 응답을 얻기 위해 새로운 과도 매개 변수가 이용하여 수식화하여 구성하였으며, 차량의 정상 상태 및 과도 특성 향상을 검증하기 위하여 ISO 기반 시뮬레이션 및 차량 실험을 수행하였다. 마지막으로 요 제어기와 횡 슬립 각도 제어기로 구성된 MASMC (Multiple Adaptive Sliding Mode Control) 접근 방식을 사용하는 4륜 모터 시스템을 사용한 동적 토크벡터링 제어를 수행하였다. 높은 비선형 특성을 가진 차량의 전후륜 타이어의 코너링 강성은 적응제어기법을 이용하여 예측하였다. 따라서, 안전모드와 다이나믹 모드를 구성하여, 운전자로 하여금 원하는 주행의 조건에 맞게 선택할 수 있는 알고리즘을 구현하였다. 이 MASMC 알고리즘은 향후 전동화 차량에 주행안정성 향상과 다이나믹한 주행의 즐거움을 주는 기술로써, 전차량 시뮬레이션을 이용하여 검증하였다.In the last ten decades, vehicle stability control systems have been dramatically developed and adapted in many commercial vehicles to avoid fatal crashes. Significantly, ESC (Electric Stability Control) system can help escape the accident from unstable driving conditions with dangerous roads such as slippery roads due to inclement weather conditions. However, for the high performed vehicle, frequent intervention from ESC reduces the pleasure of fun-to-drive. Recently, the development of traction control technologies has been taking place with that of the electrification of vehicles. The IWMs (In-Wheel Motor system), which is one of the systems that can apply independent drive of each wheel, for the limit handling characteristics, which are the operation areas of the ESC, is introduced for the control that enables the lateral characteristics of the vehicle dynamics. Firstly, the automated drift control algorithm can be proposed for the nonlinear limit handling condition of vehicles. This approach can give an insight of fun-to-drive mode to TV (Torque Vector) control scheme, but also the stability control of high sideslip angle of the vehicle on slippery roads. Secondly, using IWMs system with front two motors, understeer gradient of vehicle, which is the unique characteristics of vehicle can be used for the proposed control strategy. A new transient parameter is formulated to be acquired rapid response of controller and reducing chattering effects. Simulation and vehicle tests are conducted for validation of TV control algorithm with steady-state and transient ISO-based tests. Finally, dynamic torque vectoring control with a four-wheel motor system with Multiple Adaptive Sliding Mode Control (MASMC) approach, which is composed of a yaw rate controller and sideslip angle controller, is introduced. Highly nonlinear characteristics, cornering stiffnesses of front and rear tires are estimated by adaptation law with measuring data. Consequently, there are two types of driving modes, the safety mode and the dynamic mode. MASMC algorithm can be found and validated by simulation in torque vectoring technology to improve the handling performance of fully electric vehicles.Chapter 1 Introduction 7 1.1. Background and Motivation 7 1.2. Literature review 11 1.3. Thesis Objectives 15 1.4. Thesis Outline 15 Chapter 2 Vehicle dynamic control at limit handling 17 2.1. Vehicle Model and Analysis 17 2.1.1. Lateral dynamics of vehicle 17 2.1.2. Longitudinal dynamics of vehicle 20 2.2. Tire Model 24 2.3. Analysis of vehicle drift for fun-to-drive 28 2.4. Designing A Controller for Automated Drift 34 2.4.1. Lateral controller 35 2.4.2. Longitudinal Controller 37 2.4.3. Stability Analysis 39 2.4.4. Validation with simulation and test 40 Chapter 3 Torque Vectoring Control with Front Two Motor In-Wheel Vehicles 47 3.1. Dynamic Torque Vectoring Control 48 3.1.1. In-wheel motor system (IWMs) 48 3.1.2. Dynamic system modeling 49 3.1.3. Designing controller 53 3.2. Validation with Simulation and Experiment 59 3.2.1. Simulation 59 3.2.2. Vehicle Experiment 64 Chapter 4 Dynamic handling control for Four-wheel Drive In-Wheel platform 75 4.1. Vehicle System Modeling 76 4.2. Motion Control based on MASMC 78 4.2.1. Yaw motion controller for the inner ASMC 80 4.2.2. Sideslip angle controller for the outer ASMC 84 4.3. Optimal Torque Distribution (OTD) 88 4.3.1. Constraints of dynamics 88 4.3.2. Optimal torque distribution law 90 4.4. Validation with Simulation 91 4.4.1. Simulation setup 91 4.4.2. Simulation results 92 Chapter 5 Conclusion and Future works 104 5.1 Conclusion 104 5.2 Future works 106 Bibliography 108 Abstract in Korean 114박

A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed

Multi-objective optimisation for battery electric vehicle powertrain topologies

Electric vehicles are becoming more popular in the market. To be competitive, manufacturers need to produce vehicles with a low energy consumption, a good range and an acceptable driving performance. These are dependent on the choice of components and the topology in which they are used. In a conventional gasoline vehicle, the powertrain topology is constrained to a few well-understood layouts; these typically consist of a single engine driving one axle or both axles through a multi-ratio gearbox. With electric vehicles, there is more flexibility, and the design space is relatively unexplored. In this paper, we evaluate several different topologies as follows: a traditional topology using a single electric motor driving a single axle with a fixed gear ratio; a topology using separate motors for the front axle and the rear axle, each with its own fixed gear ratio; a topology using in-wheel motors on a single axle; a four-wheel-drive topology using in-wheel motors on both axes. Multi-objective optimisation techniques are used to find the optimal component sizing for a given requirement set and to investigate the trade-offs between the energy consumption, the powertrain cost and the acceleration performance. The paper concludes with a discussion of the relative merits of the different topologies and their applicability to real-world passenger cars

Comparison of Direct Multiobjective Optimization Methods for the Design of Electric Vehicles

"System design oriented methodologies" are discussed in this paper through the comparison of multiobjective optimization methods applied to heterogeneous devices in electrical engineering. Avoiding criteria function derivatives, direct optimization algorithms are used. In particular, deterministic geometric methods such as the Hooke & Jeeves heuristic approach are compared with stochastic evolutionary algorithms (Pareto genetic algorithms). Different issues relative to convergence rapidity and robustness on mixed (continuous/discrete), constrained and multiobjective problems are discussed. A typical electrical engineering heterogeneous and multidisciplinary system is considered as a case study: the motor drive of an electric vehicle. Some results emphasize the capacity of each approach to facilitate system analysis and particularly to display couplings between optimization parameters, constraints, objectives and the driving mission

A Real-time Nonlinear Model Predictive Controller for Yaw Motion Optimization of Distributed Drive Electric Vehicles

This paper proposes a real-time nonlinear model predictive control (NMPC) strategy for direct yaw moment control (DYC) of distributed drive electric vehicles (DDEVs). The NMPC strategy is based on a control-oriented model built by integrating a single track vehicle model with the Magic Formula (MF) tire model. To mitigate the NMPC computational cost, the continuation/generalized minimal residual (C/GMRES) algorithm is employed and modified for real-time optimization. Since the traditional C/GMRES algorithm cannot directly solve the inequality constraint problem, the external penalty method is introduced to transform inequality constraints into an equivalently unconstrained optimization problem. Based on the Pontryagin’s minimum principle (PMP), the existence and uniqueness for solution of the proposed C/GMRES algorithm are proven. Additionally, to achieve fast initialization in C/GMRES algorithm, the varying predictive duration is adopted so that the analytic expressions of optimally initial solutions in C/GMRES algorithm can be derived and gained. A Karush-Kuhn-Tucker (KKT) condition based control allocation method distributes the desired traction and yaw moment among four independent motors. Numerical simulations are carried out by combining CarSim and Matlab/Simulink to evaluate the effectiveness of the proposed strategy. Results demonstrate that the real-time NMPC strategy can achieve superior vehicle stability performance, guarantee the given safety constraints, and significantly reduce the computational efforts

Time-optimal Control Strategies for Electric Race Cars with Different Transmission Technologies

This paper presents models and optimization methods to rapidly compute the achievable lap time of a race car equipped with a battery electric powertrain. Specifically, we first derive a quasi-convex model of the electric powertrain, including the battery, the electric machine, and two transmission technologies: a single-speed fixed gear and a continuously variable transmission (CVT). Second, assuming an expert driver, we formulate the time-optimal control problem for a given driving path and solve it using an iterative convex optimization algorithm. Finally, we showcase our framework by comparing the performance achievable with a single-speed transmission and a CVT on the Le Mans track. Our results show that a CVT can balance its lower efficiency and higher weight with a higher-efficiency and more aggressive motor operation, and significantly outperform a fixed single-gear transmission.Comment: 5 pages, 4 figures, submitted to the 2020 IEEE Vehicle Power and Propulsion Conferenc