Proceedings of the Institution of Mechanical Engineers,Part D: Journal of Automobile Engineering

This paper presents an interval optimization method to improve the design robustness of the decoupling layout and frequency allocation of powertrain mounting systems (PMSs). The effects of the uncertainties or variations of the powertrain inertia properties and design parameters on the optimization results are considered in the optimization process. Generally, it is difficult and costly to determine statistical information with sufficient precision for uncertain parameters, so here interval numbers are used to describe the uncertain parameters and only the bounds of them are required. Robustness indices of interval reliability and interval possibility degree are suggested for characterizing the robustness of PMS decoupling layout and frequency allocation respectively. The interval optimization problem is transformed to an equivalent deterministic one based on the robustness indices. The optimization results of a PMS show that the interval optimization method can significantly increase the robustness of the frequency allocation, especially in vertical and pitch directions. This will decrease the possibility of resonance between the powertrain and other parts, such as the wheel, car body, and frame. In contrast to the deterministic optimization method, although the decoupling ratios obtained by the proposed method decrease slightly, the interval optimization results can meet the decoupling layout requirement from the viewpoint of engineering.

From a structural standpoint, motorbike forks must withstand the most diverse loading conditions that the normal use of the vehicle implies. By means of experimental analyses, the authors found the emergency braking to be the most severe loading case. This contribution presents a novel analytical model that, given a few geometric parameters of the motorbike and of the fork, allows calculation of the stress field on the legs under braking. The analytical model was designed to account for the unequal stress distribution on the two legs that arises from the geometrical asymmetry of single brake disc architectures. The model accuracy was tested by comparison with finite element analysis (FEA) and experimental stress analyses. Finally, the possibility of balancing the loads on the legs of single disc architectures was examined and some structural optimization strategies were proposed.

In this paper, a mathematical model for the developed electromagnetic suspension actuator is established based on measured parameters and test data. A main/inner-loop control strategy is proposed for its active control and the inner loop undertakes the control of a three-phase motor by applying a hysteresis current control method to track the calculated signal by the main loop. With the simplification of the inner-loop control system, the achievable range of control current and energy flow states of the actuator are analysed. Then, owing to the non-linear damping characteristic of the actuator, a hybrid system model which involves real and integer variables is built up for the main loop and optimal control to improve vehicle ride comfort is carried out based on a model predictive control method. Simulations are carried out with bump impulse and random uneven road inputs and the results demonstrate that the electromagnetic suspension with the designed hybrid controller can improve vehicle ride comfort compared with a corresponding passive suspension while energy is consumed from the battery.

This paper presents a parametric study of the injury risk in collisions of race cars designed for the European Formula Student competition. The study is motivated by the fact that only a limited assessment of driver safety is required for this competition. The approach was to model a Formula Student car in a mathematical dynamic model environment. A parametric study was then carried out to investigate the sensitivity of injury to various system variables. These were the crash pulse, the occupant stature, and the occupant posture. These system variables, under close examination, can be changed to alter the occupant kinematics or, in other words, they change the injury risk. The results of the analysis showed that the risk of injury in a frontal impact was dependent on the system variables. The risk of an abbreviated injury scale (AIS)2+ injury was 22.3 per cent in the baseline constant-g test, increasing to 35.2 per cent in the worst case. For AIS3+ the values were 5.1 per cent and 11 per cent, respectively. The study also showed that the occupant restraint conditions in a Formula Student car had a significant influence on the distribution of the injury risk between the body regions. The variation in the injury risk highlighted by this study, both in absolute terms and in the distribution between the body regions, showed that there are limitations to the use of vehicle kinematics in their current guise as a predictive tool for the injury risk. The results of this study represent a significant step in the understanding of the injury risk in a Formula Student frontal impact.

Robust vehicle design for improved reliability and quality has been one of the key areas of interest in the automotive industry for a number of years. Based on this approach, reliability is designed into the vehicle following a rigorous vehicle design and development process coupled with appropriate design methods, such as failure mode and effects analysis (FMEA), quality function deployment (QFD), design of experiments (DoE), the Taguchi method, and others. While significant progress has been achieved to date in improving the reliability and quality of vehicles, there is still some need to incorporate parts and subsystems with specific reliability functions within the vehicle system reliability model early in the design concept stage and throughout the vehicle design process so that the reliability of systems and subsystems can be designed-in with more confidence. A comprehensive design for reliability model for critical vehicle systems and subsystems coupled with the failure mode and effects analysis (FMEA) method could help identify and alleviate potential failure modes, and hence maximize vehicle reliability. This article proposes a design for reliability process that aims to achieve this particular outcome in the case of a mechanical vehicle transmission system. A detailed case study involving design for reliability of a vehicle transmission system is presented.

In this paper, a model-based boost pressure control of a turbocharged common-rail directed injected diesel engine is proposed. An advanced linear parameter varying (LPV) technique is adopted for model development and an H_∞ control scheme is synthesized for control purposes. The LPV technique has an advantage in deriving a linear model from a complex non-linear system and guarantees higher linear model precision. The boost pressure model of the diesel engine is obtained as a simple second-order linear system and the parameters of the model are estimated by the LPV identification method. With the help of the LPV modelling method, the behaviour of boost pressure of the diesel engine is precisely characterized using a second-order linear model. Based on the simplified LPV boost pressure model, a robust H_∞ controller is synthesized. The state-space representation is derived to follow the control design framework of an H_∞ scheme, and weighting functions for improving control performance are added into the closed-loop control system. The experimental results show that the LPV model-based diesel engine boost pressure control allows better tracking performance than the production engine management system (EMS), which requires difficult calibration work.

Hypoid gears are used in rear drive and four-wheel drive (4WD) vehicle axles. For this reason, hypoid gear whine noise has long been recognized as a problem, but there have been few or no studies of problem-solving techniques or procedures. This study analysed the possible causes of hypoid gear whine noise for its reduction and investigated the data that should be considered for the optimal shape design of hypoid gears in axle-based vehicles and the procedures for using the data for optimization. For these purposes, a hot deflection test was performed, using an actual gear mounting and the temperature of a cast-aluminium axle housing, with completely processed gear. This test covered the operating range of gear loads, from ‘no load’ to ‘peak load’. Under peak load conditions, the contact pattern extended to the tooth boundaries without showing a concentration at any point on the tooth surface. The transmission error was tested on an axle assembly triaxial real car load and at the correct temperature condition of the axle housing.

This paper is an investigation of the role of the robust control strategy of the rear wheel steer system to improve handling. To establish an accurate model of the vehicle, a nine degree-of-freedom (DOF) model is considered. The model’s degrees of freedom consist of three angular motions (roll, pitch, and yaw) of the sprung mass, spin of the wheels, and two translational motions (forward and side travel) of the unsprung mass. Also, the environment and geometric effects, such as aerodynamic forces, tyre–ground interaction, body roll versus camber relation, steering command saturation, and roll axis inclination, are taken into account. The front and rear suspensions are assumed to be a MacPherson strut and semi-trailing arm respectively. Cornering behaviour of the vehicle is studied and compared for a manual two-wheel steer (2WS) and a sliding-mode control assisted four-wheel steer (4WS) vehicle. A 3-DOF vehicle model is used to make a fast state estimation. The yaw rate is used as the reference signal for the control system, to ensure that the desired handling is obtained. The results show that during the standard cornering manoeuvres, the sliding-mode control provides significant tracking performance and lower sensitivity to vehicle velocity, road condition, and roll axis inclination compared to the 2WS. Also lane tracking and cornering behaviour of the steering system is enhanced towards the neutral steer.

Degradation of catalyst performance with time is described as ageing. There are two significant ageing mechanisms: poisoning and sintering. Experimental data on ageing have been obtained on an engine test bed using a specially designed catalyst core holder; the catalyst samples were subjected to different accelerated ageing regimes and durations. The ageing regimes were as follows: low temperature dosed (mainly poisoning); high temperature not dosed (mainly sintering); high temperature dosed (both sintering and poisoning). The experiments provided a series of samples from which the spatial and time dependences of the poisoning have been found. Portions of the samples were subjected to X-ray fluorescence analysis after ageing. A combined model of poisoning and sintering was developed and incorporated into a computational fluid dynamics model. This combined model can predict the level of deactivation as a function of length along the catalyst and as a function of time. Agreement between measured poison accumulation and predictions was achieved by tuning the sintering parameter.

Diesel engines produce a variety of particles generically classified as diesel particulate matter (PM) owing to incomplete combustion. The increasingly stringent emissions regulations require that engine manufacturers must continue to reduce the PM. The ability to predict the PM emissions is one of the key technologies that could be used in a PM reduction strategy. This paper describes a predictive technique that can be used as a virtual sensor for monitoring PM emissions in both steady and transient states for a medium- or heavy-duty diesel engine. The predictive structure is stable over a broad range of engine operation points. The input parameters are chosen on the basis of the PM formation mechanism, physical knowledge of the process, and an insight into the underlying physics. Principal-component analysis (PCA) is used to reduce the dimensionality of the inputs of a non-linear autoregressive model with exogenous inputs (NLARX) from nine inputs to five inputs. PCA not only reduces the input number but also improves the performance of the prediction model. The results show that the NLARX model could predict the particulate matter successfully with an R² value above 0.99 with only five inputs.

A complex task regarding the control of the homogeneous charge compression ignition (HCCI) combustion process is the control of combustion timing, represented by the crank angle at which 50 per cent of the fuel mass inside the cylinder is burned (MFB50). The most important parameters for transient MFB50 control are the mass of (hot) residual gas inside the cylinder (e.g. retained by internal exhaust gas recirculation), the injection strategy (in the case of direct fuel injection), and the spark timing. In this paper, the potential of a corona ignition system is examined in comparison with a conventional spark ignition system for the HCCI combustion process. For this purpose, thermodynamic investigations have been carried out on a single-cylinder research engine, combined with one-dimensional gas exchange analyses and high-speed visualization of combustion in a transparent engine. It could be demonstrated that both ignition systems are capable of influencing the autoignition process. The corona ignition system, however, allows a much later ignition point for achieving the same MFB50. This is due to the spatial character of the initial ignition area of corona ignition. In addition, the corona ignition system is more robust with respect to a change in the boundary conditions, such as a variation in the residual gas rate or the mixture composition. It is therefore more reliable in initiating autoignition, even in critical operating conditions. Additionally, it was found that the corona ignition system permits the combustion to be influenced by means of a variation in the ignition energy, which appeared to be not the case for the conventional ignition system.