Manivannan P. V.

In this work an Engine Management System (EMS) using a low cost 8-bit microcontroller specifically for the cost sensitive small two-wheeler application was designed and developed. Only the Throttle Position Sensor (TPS) and the cam position sensor (also used for speed measurement) were used. A small capacity 125CC four stroke two-wheeler was converted into a Port Fuel Injected (PFI) engine and was coupled to a fully instrumented Eddy Current Dynamometer. Air-fuel ratio was controlled using the open loop, lookup-table [speed (N) and throttle (α)] based technique. Spark Time was controlled using a proportional / fuzzy logic based close loop control algorithm for the idle speed control to reduce fuel consumption and emissions. Test results show a significant improvement in engine performance over the original carbureted engine, in terms of fuel consumption, emissions and idle speed fluctuations. The Proportional controller resulted in significantly lower speed fluctuations and HC / CO emissions than the fuzzy logic controller. Though the fuzzy logic controller resulted in low cycle by cycle variations than the original carbureted engine, it leads to significantly higher HC levels. The performance fuzzy logic can be improved by modifying the membership function shapes with more engine test data. Copyright © 2007 by ASME.

Semi-active suspension is widely used in automotive applications, as it is providing good ride quality at reasonably low cost. Among the various methods available for enhancing ride comfort, magnetorheological (MR) suspension has drawn much attention due to its robustness and fail-safe nature as compared to electrorheological suspension. In semi-active suspension, the damping coefficient of the MR damper is varied by modulating the current supplied to damper coil. In the present work, a quarter car with semi-active suspension system is modeled and its performance is studied through simulation under the MATLAB / Simulink environment. A hybrid control algorithm consisting of differential flatness along with LQR (linear quadratic regulator) is proposed to vary the current input for the magnetorheological damper for reducing the sprung mass acceleration, jerk and to improve ride quality. The simulation results also show that the performance of semi-active suspension that uses magnetorheological damper along with developed hybrid algorithm is superior to the LQR controlled suspension, when subjected to random road profiles.

A two-degree freedom air fuel ratio controller (Model based feed forward transient plus closed loop Proportional Integral-Derivative (PID) steady state controllers) developed for controlling the air fuel ratio of the charge in a small displacement (125 CC) SI engine is presented. The feed forward controller's airflow and injector models were developed after conducting extensive experiments on the engine modified for the Port Fuel Injection (PFI) operation. A dynamic air fuel ratio model obtained (air fuel ratio changes measured using an UEGO sensor) by injecting the Pseudo Random Binary Signal (PRBS) signal in addition to base line fuel injection pulse, was used for designing the PID controller. Optimal PID gain values were identified using Nelfer-Mead optimization technique. The control algorithms were implemented and optimized using SIMULINK blocks that are run under dSPACE on the MicroAuto box hardware. The optimized control algorithms were ported on the specially designed, in-house built, low cost engine management system (EMS) developed around an 8-bit microcontroller. The spark timing was also controlled simultaneously for knock free operation. The two-degree freedom air fuel ratio controller could maintain the air fuel ratio under steady and transient conditions closely. High thermal efficiency and low HC & NOx emissions were achieved using the developed EMS. At higher speed elevated NOx emission was observed, due to the use of leaner mixture. The improvements are expected to be higher if a suitable smaller injector is used. Copyright © 2012 by ASME.

During a cornering manoeuvre, in a vehicle equipped with Ackerman steering geometry, the inner tire operates at a higher slip angle relative to the outer tire. As lateral load transfer occurs, the potential of the inner tires to produce the lateral force reduces and with systems like active steering, the saturation of lateral force occurs even earlier. In order to have an ideal steering geometry, at low speeds the system should follow Ackerman geometry closely and at higher speeds it should follow anti-Ackerman geometry. The tire workload (TW) distribution is a critical variable to be analyzed to prevent tire force saturation. The present paper aims to formulate the wheel angle relation for front wheel steering based on tire workload distribution. The tire workload difference (TWD) between the steered wheels is chosen as the active variable to arrive at the wheel angle relation. To study the transient behavior of the vehicle with tire workload redistribution (TWR), the Mimuro plot is used. The developed wheel angle relation utilizes the tire forces effectively and the results show improved cornering performance of the vehicle. This type of study which accounts for balancing tire workload for both lower and higher cornering speeds based on wheel angle relation has not been reported earlier in literature.

Using SONAR as the primary range finding sensor has largely been abandoned due to problems such as limited range, large bearing errors and large beam widths. However, SONAR is used conjunction with other sensors such as LIDARs, RADARs and vision sensors for ranging and obstacle avoidance in many autonomous vehicle applications. In this paper, we propose a solution to reduce the range and bearing error significantly, and thus improve the performance of the SONAR. Using the results from the Gaussian Correlation Inequality, we derive probabilistic transformations that can improve the range and bearing measurement of the SONAR, thus reducing the sensor error. We are also presenting simulation study, to place bounds on the types and characteristics of the SONARs within which our model's performance is optimal.

An idle speed engine model has been proposed and applied for the development of an idle speed controller for a 125 cc two wheeler spark ignition engine. The procedure uses the measured Indicated Mean Effective Pressure (IMEP) at different speeds at a constant fuel rate and throttle position obtained by varying the spark timing. At idling conditions, IMEP corresponds to the friction mean effective pressure. A retardation test was conducted to determine the moment of inertia of the engine. Using these data, a model for simulating the idle speed fluctuations, when there are unknown torque disturbances, was developed. This model was successfully applied to the development of a closed loop idle speed controller based on spark timing. The controller was then implemented on a dSPACE Micro Autobox on the actual engine. The Proportional Derivative Integral (PID) controller parameters obtained from the model were found to match fairly well with the experimental values, indicating the usefulness of the developed idle speed model. Finally, the optimized idle speed control algorithm was embedded in and successfully demonstrated with an in-house built, low cost engine management system (EMS) specifically designed for two-wheeler applications. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

In this work an Engine Management System (EMS) using a low cost 8-bit microcontroller specifically for the cost sensitive small two-wheeler application was designed and developed. Only the Throttle Position Sensor (TPS) and the cam position sensor (also used for speed measurement) were used. A small capacity 125CC four stroke two-wheeler was converted into a Port Fuel Injected (PFI) engine and was coupled to a fully instrumented Eddy Current Dynamometer. Air-fuel ratio was controlled using the open loop, lookup-table [speed (N) and throttle (α)] based technique. Spark Time was controlled using a proportional / fuzzy logic based close loop control algorithm for the idle speed control to reduce fuel consumption and emissions. Test results show a significant improvement in engine performance over the original carbureted engine, in terms of fuel consumption, emissions and idle speed fluctuations. The Proportional controller resulted in significantly lower speed fluctuations and HC / CO emissions than the fuzzy logic controller. Though the fuzzy logic controller resulted in low cycle by cycle variations than the original carbureted engine, it leads to significantly higher HC levels. The performance fuzzy logic can be improved by modifying the membership function shapes with more engine test data.

This paper presents a novel Simplified Node decomposition and Platoon (SNAP) head selection cluster-based routing algorithm for Vehicular Ad hoc Networks (VANET) communication. The major novelty of the paper is the two proposed algorithms through which the number of platoons and platoon heads (PH) are decided upon for increasing the network lifetime. Algorithm-1 analyze the distribution of nodes and forms a set of possible minimum number of platoons (clusters) having equal number nodes, based on Hierarchical clustering technique. The algorithm-2 partitions the given network into platoons and selects the platoon head (PH) based on coverage range of wireless node. It uses SPSS statistical software tool for platoon decomposition and also to determine the platoon head (PH). The number of iterations required for selection of PH is found to be minimum, irrespective of the number of network nodes. The platoon is controlled by its platoon head (PH) and the data transfer happens locally between the platoon nodes and its head. The platoon head alone communicates with the road side unit (RSU) and avoids multiple data link between the individual nodes of platoon to RSU. The performance of SNAP algorithm has been verified using NS-2 network simulator and found to consume less transmission energy, increased node and network lifetime which in turn increase the overall efficiency of the network.

We report a planar solenoid actuated valveless micropump with multiple inlet-outlet configurations. The self-priming characteristics of the multiple inlet-multiple outlet micropump are studied. The filling dynamics of the micropump chamber during start-up and the effects of fluid viscosity, voltage and frequency on the dynamics are investigated. Numerical simulations for multiple inlet-multiple outlet micropumps are carried out using fluid structure algorithm. With DI water and at 5.0 Vp-p, 20 Hz frequency, the two inlet-two outlet micropump provides a maximum flow rate of 336 μl min-1 and maximum back pressure of 441 Pa. Performance characteristics of the two inlet-two outlet micropump are studied for aqueous fluids of different viscosity. Transport of biological cell lines and diluted blood samples are demonstrated; the flow rate-frequency characteristics are studied. Viability of cells during pumping with multiple inlet multiple outlet configuration is also studied in this work, which shows 100% of cells are viable. Application of the proposed micropump for simultaneous pumping, mixing and distribution of fluids is demonstrated. The proposed integrated, standalone and portable micropump is suitable for drug delivery, lab-on-chip and micro-total-analysis applications.

A cognitive decision making algorithm, which tries to emulate human driver behaviour, for autonomous vehicles is presented in this paper. The decision making process, as well as the integration of the decision making with real time control in different traffic scenarios is studied through simulations using vehicle dynamics model for a car like vehicle. The decision making algorithm was found to perform better, when integrated with the ANFIS Fuzzy Logic longitudinal Control than with conventional PID control. The simulation results with the different traffic scenarios demonstrate the successful integration of the real time control and decision making modules of the Intelligent Vehicle Architecture.