Torque control of engine clutch to improve the driving quality of hybrid electric vehicles

As a powertrain for hybrid electric vehicles (HEVs), the automatic transmission (AT) is not only convenient for the driver but also reduces hybridization costs because the existing production line is used to produce the AT. However, it has low fuel economy due to the torque converter. To overcome this disadvantage, this paper studies HEVs equipped an AT without a torque converter. In this case, additional torque control is needed to prevent the driving quality from deteriorating. This paper suggests three different torque control methods and develops a simulator for an HEV that can simulate the dynamic behaviors of the HEV when the engine clutch is engaged. The HEV drive train is modeled with AMESim, and a controller model is developed with MATLAB/Simulink. A co-simulation environment is established. By using the developed HEV simulator, simulations are conducted to analyze the dynamic behaviors of the HEV according to the control methods.     

用于电动和混合动力交通工具的功率模块

对减少CO2排放的急迫呼吁,已使主要的汽车制造商致力于开发新的电动和混合动力驱动交通工具解决方案。为这些应用开发功率半导体模块,需要新的模块集成和封装解决方案。     

插电式混合动力汽车现状

本文介绍了插电式混合动力汽车的发展背景、工作模式、动力系统结构。阐叙了PHEV对动力电池的性能要求,提出了当前PHEV研究所面临的问题。     

Advanced hybrid energy storage system for mild hybrid electric vehicles

Hybrid electric vehicles (HEV) utilize electric power and a mechanical engine for propulsion; therefore, the performance of HEVs is directly influenced by the characteristics of the energy storage system (ESS). The ESS for an HEV generally requires high power performance, long cycle life, reliability and cost effectiveness; thus, a hybrid energy storage system (HESS) that combines different types of storage devices has been considered to fulfill both performance and cost requirements. To improve the operating efficiency and cycle life of a HESS, an advanced dynamic control regime in which pertinent storage devices in the HESS can be selectively operated based on their status is presented. Verification tests were performed to confirm the degree of improvement in energy efficiency. In this paper, an advanced HESS with a battery management system (BMS) that includes an optimal switching control function based on the estimated state of charge (SOC) is presented and verified.     

Modeling and model predictive control for hybrid electric vehicles

This paper builds up a typical model of a parallel hybrid electric vehicle and develops model predictive controllers for this model to control the speeds and torques for fast clutch engagement with high driving comfort and low jerk. Some modified algorithms for model predictive controllers are studied to improve their ability to track the desired speed setpoints, subject to input and output constraints.     

An optimal torque distribution control strategy for four-independent wheel drive electric vehicles

In this paper, an optimal torque distribution approach is proposed for electric vehicle equipped with four independent wheel motors to improve vehicle handling and stability performance. A novel objective function is formulated which works in a multifunctional way by considering the interference among different performance indices: forces and moment errors at the centre of gravity of the vehicle, actuator control efforts and tyre workload usage. To adapt different driving conditions, a weighting factors tuning scheme is designed to adjust the relative weight of each performance in the objective function. The effectiveness of the proposed optimal torque distribution is evaluated by simulations with CarSim and Matlab/Simulink. The simulation results under different driving scenarios indicate that the proposed control strategy can effectively improve the vehicle handling and stability even in slippery road conditions.     

Motor control of input-split hybrid electric vehicles

A motor control strategy for an input-split hybrid electric vehicle (HEV) is proposed. From a power characteristic analysis, it is found that the powertrain efficiency decreases for speed ratios at which power circulation occurs. Using dynamic models of an input-split HEV powertrain, a motor-generator control algorithm for obtaining high system efficiency is designed by inversion-based control. The performance of the control algorithm is evaluated by the simulator which is developed based on PSAT, and simulation results are compared with the test results. It is found that, even if the engine thermal efficiency is sacrificed by moving the engine operation point from the OOL for the control strategy, improved overall powertrain system efficiency can be achieved by the engine operation that gives a relatively high efficiency from the viewpoint of the overall powertrain efficiency. The control algorithm developed can be used in design of future electric vehicles.     

Performance analysis of a CVT clutch system for a hybrid electric vehicle

In this study, the performance of a CVT clutch system for a hybrid electric vehicle was investigated. To analyzed the vehicle performance at restart, the restart delay and driveshaft torque was investigated by simulations and experiments. It was found from the simulation results that the vehicle restart response depends on the clutch pressure buildup time to the point where the clutch torque begins to overcome the vehicle road load, and driving comfort at restart is directly related to the rate change of the clutch pressure.     

混合动力电动汽车研究开发及前景展望

随着世界石油资源逐渐贫乏,寻求新能源已成为解决石油危机的必然选择.混合动力电动汽车应运时代的要求,逐步走向规模化和产业化.本文主要介绍混合动力电动汽车的不同种类车型的特点,并对混合动力电动汽车的发展作出了大胆的展望.     

Direct method for optimal power management in hybrid electric vehicles

Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed.     

Kriging assisted on-line torque calculation for brushless DC motors used in electric vehicles

Torque is one of the most important control factors for a vehicle’s motion. Compared with internal combustion engines, electric motors can have a more accurate torque feedback which brings a lot of advantages to vehicle dynamics and stability control. However, motors used in electric vehicles are facing more difficult conditions than those in conventional applications, such as extreme high/low temperature changing, vibration, aging, etc. The variation of motor parameters due to harsh working conditions can lead to serious problems for motor torque estimation and thus dynamic control of electric vehicles. In this paper, a new method using kriging to estimate the back EMF and thus accurately calculate motor torque in an on-line fashion is presented. With motor speed and rotor position as inputs, kriging predicts back EMF as the output that is used to calculate the motor torque with three phase currents. Using this novel method, motor torque can be accurately calculated even facing high/low temperatures or aging conditions. Experimental tests under the high temperature have been conducted to verify the applicability of the proposed method.     

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.     

Control strategy for clutch engagement during mode change of plug-in hybrid electric vehicle

The plug-in hybrid electric vehicle (PHEV) has various driving modes used in both internal combustion engine and electric motors. The EV mode uses only an electric motor and the HEV mode uses both an engine and an electric motor. Specifically, when the PHEV of a pre-transmission parallel hybrid structure performs mode changing, its engine clutch is either engaged or disengaged, which is important in terms of ride comfort. In this paper, to enhance the mode changing process for the clutch engagement, a PHEV performance simulator is developed using MATLAB/Simulink based on system dynamics and experiment data. Vehicle driving analysis is carried out of the control logic and properties of the mode changing. A compensated torque is applied during the mode change. This results in the rapid speed synchronization with the clutch although the trade-off relationship of the mode change. In addition, the mode changing is conducted through the transmission shifting process to rapidly synchronize with speed. The control strategy implemented in this study is shown to improve the drivability and energy efficiency of a PHEV.     

Development of equivalent fuel consumption minimization strategy for hybrid electric vehicles

Power distribution between an internal combustion engine and electric motors is one of main features of hybrid electric vehicles that improves their fuel economy. An equivalent fuel consumption minimization strategy can instantaneously identify the optimal power distribution by converting the battery power into the equivalent fuel power and minimizing the overall fuel consumption. To guarantee the effectiveness of the strategy, it is essential to find the proper value of the conversion factor used to obtain the equivalent fuel power. However, finding the proper value is not a straightforward process because it is necessary to consider the overall power conversion efficiencies and battery charge sustaining strategy for the target driving cycle in advance. In this study, a model-based parameter optimization method is introduced to find the optimal conversion factor. A hybrid electric vehicle simulation model capable of estimating fuel consumption was developed, and the optimal conversion factor was discovered using a genetic algorithm that evaluates its population members using the simulation model. A series of simulations and vehicle tests was conducted to verify the effectiveness of the optimized strategy, and the results show a distinct improvement in fuel economy.     

A control strategy for parallel hybrid electric vehicles based on extremum seeking

An energy management control strategy for a parallel hybrid electric vehicle based on the extremum-seeking method for splitting torque between the internal combustion engine and electric motor is proposed in this paper. The control strategy has two levels of operation: the upper and lower levels. The upper level decision-making controller chooses the vehicle operation mode such as the simultaneous use of the internal combustion engine and electric motor, use of only the electric motor, use of only the internal combustion engine, or regenerative braking. In the simultaneous use of the internal combustion engine and electric motor, the optimum energy distribution between these two sources of energy is determined via the extremum-seeking algorithm that searches for maximum drivetrain efficiency. A dynamic programming solution is also obtained and used to form a benchmark for performance evaluation of the proposed method based on extremum seeking. Detailed simulations using a realistic model are presented to illustrate the effectiveness of the methodology.     

Realization of pmp-based control for hybrid electric vehicles in a backward-looking simulation

Optimal control is generally not possible without information about the future coming up, and it is not easy to obtain an optimal solution even though the information is given a priori. In this paper, a control concept based on Pontryagin’s Minimum Principle (PMP) is introduced as an efficient solution to generate an optimal control trajectory for Hybrid Electric Vehicles (HVEs) when the performance of the vehicles is evaluated on scheduled driving cycles at a simulation level. The main idea of the control concept is to minimize Hamiltonian, which is interpreted as equivalent fuel consumption, and the Hamiltonian is characterized by a co-state, which is interpreted as a weighting factor for the electrical usage. A key aspect of the control problem is that an appropriate initial condition of the co-state is required to satisfy the boundary condition of the problem. In this study, techniques to calculate the Hamiltonian in different hybrid configurations are introduced, and a methodology to look for the initial condition of the co-state is studied, so that the controller is able to realize a desired State Of Charge (SOC) trajectory. To address the issue, we utilize a shooting method with multiple initial conditions based on the concept of the Newton-Raphson method, and all these techniques are realized in a backward looking simulator. The simulation results show that the PMP-based control is a very efficient approach to produce the optimal control trajectory, and the performance is compared to the optimal solution solved by Dynamic Programming (DP).     

Novel evaluation method of fuel consumption and emission for heavy-duty hybrid electric vehicles

This paper is a continuation of a previous paper titled “A novel way to calculate energy efficiency for rechargeable batteries” published on Journal of Power Sources/2012 describing a new method to calculate energy efficiency for rechargeable batteries. The present paper further describes the application of energy efficiency model on the evaluation of fuel consumption and emission for the heavy-duty hybrid electric vehicles (HD-HEVs). A more accurate calculation method of net energy change for power battery pack is proposed based on energy efficiency model of power battery pack. A more simplified and accurate correction method of fuel consumption and emission is also presented based on equivalent mileage. The fuel consumption and emission on chassis dynamometer are measured in the HD-HEVs. The experiment results show that relative errors of fuel consumption and emission between equivalent mileage correction results and linear regression correction results are less than 3%, which verifies accuracy and validates the proposed evaluation method for HD-HEVs fuel consumption and emission.     

串联式混合动力在城市公交运行中的优势

由于现今的城市交通拥堵出现的问题日益阻碍城市的发展,根据城市公交运行的特点出发,串联式混合动力电动汽车为可持续发展城市交通提供了一种有效的方案.     

Combined control of a regenerative braking and antilock braking system for hybrid electric vehicles

Most parallel hybrid electric vehicles (HEV) employ both a hydraulic braking system and a regenerative braking system to provide enhanced braking performance and energy regeneration. A new design of a combined braking control strategy (CBCS) is presented in this paper. The design is based on a new method of HEV braking torque distribution that makes the hydraulic braking system work together with the regenerative braking system. The control system meets the requirements of a vehicle longitudinal braking performance and gets more regenerative energy charge back to the battery. In the described system, a logic threshold control strategy (LTCS) is developed to adjust the hydraulic braking torque dynamically, and a fuzzy logic control strategy (FCS) is applied to adjust the regenerative braking torque dynamically. With the control strategy, the hydraulic braking system and the regenerative braking system work synchronously to assure high regenerative efficiency and good braking performance, even on roads with a low adhesion coefficient when emergency braking is required. The proposed braking control strategy is steady and effective, as demonstrated by the experiment and the simulation.     

Bees-algorithm-based optimization of component size and control strategy parameters for parallel hybrid electric vehicles

This paper presents the optimization of key component sizes and control strategy for parallel hybrid electric vehicles (parallel HEVs) using the bees algorithm (BA). The BA is an intelligent optimization tool that mimics the food foraging behavior of honey bees. Parallel HEV configuration and electric assist control strategy were used to conduct the research. The values of the key component size and the control strategy parameters were adjusted according to the BA to minimize the weighted sum of fuel consumption (FC) and emissions, while the vehicle performance satisfies the PNGV constraints. In this research, the software ADVISOR was used as the simulation tool, and the driving cycles FTP, ECE-EUDC and UDDS were employed to evaluate FC, emission and dynamic performance. The results demonstrate that the BA is a powerful tool in parallel HEV optimization to determine the optimal parameters of component sizes and control strategy, resulting in the improvement of FC and emissions without sacrificing vehicle performance. In addition, the BA is able to define a global solution with a high rate of convergence.