Papers by Srikanth Kolachalama
Data-centric engineering, 2022
In this article, a novel drive mode, "intelligent vehicle drive mode" (IVDM), was proposed, which... more In this article, a novel drive mode, "intelligent vehicle drive mode" (IVDM), was proposed, which augments the vehicle engine performance in real-time. This drive mode predicts the driver behavior vector (DBV), which optimizes the vehicle engine performance, and the metric of optimal vehicle engine performance was defined using the elements of engine operating point (EOP) and heating ventilation and air conditioning system (HVAC). Deep learning (DL) models were developed by mapping the vehicle level vectors (VLV) with EOP and HVAC parameters, and the trained functions were utilized to predict the future states of DBV reflecting augmented vehicle engine performance. The iterative analysis was performed by empirically estimating the future states of VLV in the allowable range of DBV and was fed into the DL model to predict the performance vectors. The defined vehicle engine performance metric was applied to the predicted vectors, and thus optimal DBV is the instantaneous output of the IVDM. The analytical and validation techniques were developed using field data obtained from General Motors Inc., Warren, Michigan. Finally, the proposed concept was quantified by analyzing the instantaneous engine efficiency (IEE) and smoothness measure of the instantaneous engine map (IEM). Vehicle drive modes were developed to augment the rider's comfort, safety and reduce fuel consumption. In this research, a novel "intelligent vehicle drive mode" (IVDM) was proposed, embedded with the functionality of obliging the driver's command in all scenarios and predicting the driver behaviour vector (DBV) for future time steps to enhance the vehicle engine performance without increasing the time of trip traversal. IVDM can be activated as a stand-alone application or in conjunction with any other drive modes, accommodating a vehicle speed >25 MPH on a regular terrain profile. The IVDM is most applicable to the vehicles built-in with advanced infotainment and connectivity features, and could potentially emerge as a new feature of the automotive system.
Using Deep Learning to Predict the Engine Operating Point in Real-Time
Vehicles
This article presents a novel methodology to predict the optimal adaptive cruise control set spee... more This article presents a novel methodology to predict the optimal adaptive cruise control set speed profile (ACCSSP) by optimizing the engine operating conditions (EOC) considering vehicle level vectors (VLV) (body parameter, environment, driver behaviour) as the affecting parameters. This paper investigates engine operating conditions (EOC) criteria to develop a predictive model of ACCSSP in real-time. We developed a deep learning (DL) model using the NARX method to predict engine operating point (EOP) mapping the VLV. We used real-world field data obtained from Cadillac test vehicles driven by activating the ACC feature for developing the DL model. We used a realistic set of assumptions to estimate the VLV for the future time steps for the range of allowable speed values and applied them at the input of the developed DL model to generate multiple sets of EOP’s. We imposed the defined EOC criteria on these EOPs, and the top three modes of speeds satisfying all the requirements are d...
A NARX model to Predict Cabin Air Temperature to Ameliorate HVAC Functionality
The vehicular technology has integrated many features in the system, which enhances the safety an... more The vehicular technology has integrated many features in the system, which enhances the safety and comfort of the user. Among these features, heating, ventilation, and air conditioning (HVAC) is the only feature that maintains the set cabin air temperature (CAT). The user’s command drives the set CAT, and the thermostat provides feedback to the HVAC to maintain the set CAT. The CAT is increased by extracting the heat from the engine surface produced by the fuel combustion, whereas the CAT is reduced by the known processes of the air conditioning system (ACS). Therefore, the CAT driven by the user’s command may not be optimal, and estimating the optimal CAT is still unsolved. In this work, the user was allowed to input a range for CAT instead of a single value. Optimal HVAC criteria were defined, and the CAT was estimated by performing iterative analysis in the user-selected range satisfying the criteria. The HVAC criteria were defined based on two measurable parameters: air conditio...
Predictive Model of ACC Speed to Enhance Engine Operating Conditions
The ACC feature when activated augments the engine performance in real-time. This article present... more The ACC feature when activated augments the engine performance in real-time. This article presents a novel methodology to predict the optimal adaptive cruise control set speed profile (ACCSSP) by considering all the effecting parameters. This paper investigates engine operating conditions (EOC) criteria to develop a predictive model of ACCSSP in real-time. We developed a deep learning (DL) model using the NARX method to predict engine operating point (EOP) mapping the vehicle-level vectors (VLV). We used real-world field data obtained from Cadillac test vehicles driven by activating the ACC feature for developing the DL model. We used a realistic set of assumptions to estimate the VLV for the future time steps for the range of allowable speed values and applied them at the input of the developed DL model to generate multiple sets of EOP’s. We imposed the defined EOC criteria on these EOPs, and the top three modes of speeds satisfying all the requirements are derived for each second....
Journal of Robotics
This paper presents a literature survey documenting the evolution of continuum robots over the pa... more This paper presents a literature survey documenting the evolution of continuum robots over the past two decades (1999–present). Attention is paid to bioinspired soft robots with respect to the following three design parameters: structure, materials, and actuation. Using this three-faced prism, we identify the uniqueness and novelty of robots that have hitherto not been publicly disclosed. The motivation for this study comes from the fact that continuum soft robots can make inroads in industrial manufacturing, and their adoption will be accelerated if their key advantages over counterparts with rigid links are clear. Four different taxonomies of continuum robots are included in this study, enabling researchers to quickly identify robots of relevance to their studies. The kinematics and dynamics of these robots are not covered, nor is their application in surgical manipulation.
Advances In Mobile Robotics - Proceedings of the Eleventh International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines, 2008
In this paper we develop a model of a Linear Force Actuator based actively articulated suspension... more In this paper we develop a model of a Linear Force Actuator based actively articulated suspension vehicle with toroidal wheels and propose a strategy to control its contact forces to improve traction on uneven terrain in 3-D while maintaining a desired posture. We develop the quasi-static analysis for our vehicle and compare the maneuverability of our vehicle with that of a passive suspension system. Extensive uneven terrain simulations depict the efficacy of our proposed system.
Determination of Optimally Stable Posture for Force Actuator Based Articulated Suspension for Rough Terrain Mobility
Communications in Computer and Information Science, 2010
... Actuator Based Articulated Suspension for Rough Terrain Mobility Vijay Eathakota, Arun KumarS... more ... Actuator Based Articulated Suspension for Rough Terrain Mobility Vijay Eathakota, Arun KumarSingh, Srikant Kolachalam, and K. Madhava Krishna International Institute of Information Technology, Hyderabad vijay@research.iiit.ac.in, aks1812@gmail.com, mkrishna@iiit.ac.in ...
Thermal Analysis of Radiator Core in Heavy Duty Automobile
Heat Transfer: Volume 2, 2008
ABSTRACT Background: Heat dissipation is one of the most critical considerations in engine design... more ABSTRACT Background: Heat dissipation is one of the most critical considerations in engine design and with an efficient cooling system; performance of the engine can be dramatically improved. All internal combustion engines convert chemical energy into mechanical power. Around 70% of the energy is converted into heat and therefore, the primary job of the cooling system is to keep the engine from overheating by transferring this heat to the air. A radiator transfer’s heat from the hot coolant to the air and an effective design of radiator will ultimately lead to enhanced engine performance by reducing the heating effect. Methods and results: A mathematical expression for the rate of heat dissipation from the radiator core was derived and a modification in the design was proposed in the radiator core by changing the structure of the tubes from cylindrical to helical. The rate of heat dissipation for both designs was compared with similar boundary conditions by varying the magnitude of all design parameters in a specific range that have same magnitude of area of cross section, length of the radiator core and coefficient of thermal conductivity for the tube. Enhanced rate of heat dissipation for helical structure confirms the efficacy of the proposed design.
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Papers by Srikanth Kolachalama