Review of flywheel based internal combustion engine hybrid vehicles

Hybrid vehicles of different configurations and utilizing different energy storage systems have existed in development for many decades and more recently in limited production. They can be grouped as parallel, series or complex hybrids. Another classification is micro, mild and full hybrids which makes the distinction on the basis of functionality. The common energy storage systems in hybrid vehicles are batteries, supercapacitors and high speed flywheels. This paper aims to review a specific type of hybrid vehicle which involves the internal combustion engine (ICE) as the prime mover and the high speed flywheel as an energy storage device. Such hybrids are now attracting considerable interest given their potential for low cost. It is hence timely to produce a review of research and development in this subject. The flywheel is coupled to the drive line with a continuous variable transmission (CVT). The CVT can be of various types such as electrical, hydraulic or mechanical but usually in this case it is a non-electrical one. Different configurations are possible and the paper provides a timeline of the development of such powertrains with various examples. These types of hybrid vehicles have existed as prototypes for many decades and the authors believe that their development has reached levels where they can be considered serious contenders for production vehicles.     

Artificial neural network approach to study the effect of injection pressure and timing on diesel engine performance fueled with biodiesel

This study intends to predict the influence of injection pressure and injection timing on performance, emission and combustion characteristics of a diesel engine fuelled with waste cooking palm oil based biodiesel using the artificial neural network (ANN) model. To acquire data for training and testing in the proposed ANN, experiments were carried out in a single cylinder, four stroke direct injection diesel engine at a constant speed of 1500 rpm and at full load (100%) condition. From the experimental results, it was observed that waste cooking palm oil methyl ester provided better engine performance and improved emission and combustion characteristics at injection pressure of 280 bar and timing of 25.5° bTDC. An ANN model was developed using the data acquired from the experiments. Training of ANN was performed based on back propagation learning algorithm. Multilayer perceptron (MLP) network was used for non-linear mapping of the input and output parameters. Among the various networks tested the network with two hidden layers and 11 neurons gave better correlation coefficient for the prediction of engine performance, emission and combustion characteristics. The ANN model was validated with the test data which was not used for training and was found to be very well correlated.     

Computational and experimental investigation of the unsteady flow structures around automotive outside rear-view mirrors

The unsteady flow field around two automotive outside rear-view mirrors is investigated. This study includes comprehensive experimental and computational approaches in order to characterize the complex flow structures in the wake of the mirrors. The experiments were carried out in a wind tunnel which included the measurements of the instantaneous and averaged velocity fields as well as mean and unsteady surface pressure distributions. The simulations were performed using Large Eddy Simulation (LES). The LES approach (particularly with the dynamic subgrid viscosity model) provided good agreements with the experiments for the velocity and the surface pressure distributions. The experimental and the computational results of this study will be used as a benchmark to validate the current and the future CFD development and the subsequent aero-acoustic computations.     

Driver curve speed model and its application to ACC speed control in curved roads

A speed control algorithm for an ACC (Adaptive Cruise Control) system for curved roads is proposed based on driver behavior characteristics. As the foundation of this research, a driver speed model for curved roads is developed using a series of experimental data regarding driver behavior. To adapt the model to each driver’s individual curve speed behavior, the coefficients of the model are identified in real time from the data sequences collected during drivers’ manual operation stage by a self-learning algorithm based on a Recursive Least-Square (RLS) method with a forgetting factor. Using this algorithm, the parameters of the driver model can be identified from the data collected in the manual operation phase, and the identification results are applied during the ACC automatic control phase. Based on the developed model, the ACC speed control algorithm is modified to provide each individual driver with a customized speed profile for the scenario of a curved road with no car ahead. Tests verify the applicability of the modified system.     

Dual extended Kalman filter for vehicle state and parameter estimation

The article demonstrates the implementation of a model-based vehicle estimator, which can be used for combined estimation of vehicle states and parameters. The estimator is realised using the dual extended Kalman filter (DEKF) technique, which makes use of two Kalman filters running in parallel, thus 'splitting' the state and parameter estimation problems. Note that the two problems cannot be entirely separated due to their inherent interdependencies. This technique provides several advantages, such as the possibility to switch off the parameter estimator, once a sufficiently good set of estimates has been obtained. The estimator is based on a four-wheel vehicle model with four degrees of freedom, which accommodates the dominant modes only, and is designed to make use of several interchangeable tyre models. The paper demonstrates the appropriateness of the DEKF. Results to date indicate that this is an effective approach, which is considered to be of potential benefit to the automotive industry.     

柴油机故障诊断专家系统知识库设计

在分析柴油机故障诊断知识特点的基础上,采用模糊化方法对柴油机运行状态参数进行处理,采用综合型知识方式来表达柴油机故障诊断知识,采用多库多层次的方式组织知识库,并对知识库采取一系列方式进行管理与维护。应用表明,柴油机故障诊断专家系统的预报准确率较高,具有较强的实用性。     

Estimation of maximum road friction coefficient based on Lyapunov method

With the real time and accurate information of motor torque and rotation speed of the four-in-wheel-motordrive electric vehicles, a slip based algorithm for estimating maximum road friction coefficient is designed using Lyapunov stability theory. Modified Burckhardt tire model is used to describe longitudinal slip property of the tire. By introducing a new state variable, a nonlinear estimator is proposed to estimate the longitudinal tire force and the maximum road friction coefficient simultaneously. With the appropriate selection of estimation gain, the convergence of the estimation error of the tire longitudinal force and maximum road friction coefficient is proved through Lyapunov stability analysis. In addition, the error is exponentially stable near the origin. Finally the method is validated with Carsim-Simulink co-simulation and real vehicle tests under multi working conditions in acceleration situation which demonstrate high computational efficiency and accuracy of this method.     

Cycle-simulation turbulence modelling of IC engines

Numerical simulations of IC engines are of high interest for automotive engineers worldwide. The simulation models should be as fast as possible, low-computational effort and predictive tool. The correct prediction of turbulence level inside the combustion chamber of spark ignition engines is the most important factor influencing to the engine working cycle. This paper presents a development of the k-ε turbulence model applied to the commercial cycle-simulation software with the high emphasis on the intake part. The validation was performed on two engine geometries with the variation of engine speed and load comparing the cycle-simulation results of the turbulent kinetic energy and in-cylinder temperature with 3-D CFD results. In order to apply the cycle-simulation turbulence model for the simulation of entire engine map, the parameterization model of turbulence constants was proposed. The parameterized turbulence model was optimized using NLPQL optimization algorithm where the single set of turbulence model parameters for each engine was found. A good agreement of the turbulent kinetic energy during the expansion was achieved when the turbulence affects the flame front propagation and combustion rate as well.     

Clamping performance of fastener in windshield wiper assembly using theoretical and experimental methods

Improper clamping of wiper arms can cause problems in the operation of the wiper. An excessive clamping force can cause damage to the wiper arm head. On the other hand, an insufficient clamping force can cause self-loosening of the nut. Given the lack of direct research on the clamping force of the fastener in wiper assembly, this study verifies the existing clamping performance of the fastener in windshield wiper assembly by theoretical and experimental methods. The theoretical calculation results show that all the clamping performance are satisfied under the general snow load condition. However, under the critical load condition, maximum assembly preload and safety margin against slipping are in disagreement with the standard values. This problem is solved by increasing the strength grade of the bolt. The experimental results show a reducing tendency of the clamping force during the snow durability test. However, this reducing clamping force during the 60,000 test cycles is acceptable. In the case of nut reusing more than two times possibly cause a problem of its loosening because of insufficient clamping force. Therefore, it is recommended that the nut should not be reused more than two times.     

Application of a modified thermostatic control strategy to parallel mild HEV for improving fuel economy in urban driving conditions

A modified thermostatic control strategy is applied to the powertrain control of a parallel mild hybrid electric vehicle (HEV) to improve fuel economy. This strategy can improve the fuel economy of a parallel mild HEV by operating internal combustion engine (ICE) in a high-efficiency region. Thus, in this study, experiments of a parallel mild HEV were conducted to analyze the characteristics of the hybrid electric powertrain and a numerical model is developed for the vehicle. Based on the results, the thermostatic control strategy was modified and applied to the vehicle model. Also, battery protection logic by using electrochemical battery model is applied because the active usage of battery by thermostatic control strategy can damage the battery. The simulation results of the vehicle under urban driving conditions show that the thermostatic control strategy can improve the vehicle’s fuel economy by 3.7 % compared with that of the conventional strategy. The results also suggest that the trade-off between the fuel economy improvement by efficient ICE operation and the battery life reduction by active battery usage should be carefully investigated when a thermostatic control strategy is applied to a parallel mild HEV.