Wheel Slip Regulation (WSR) is one of the Active Vehicle Safety Systems (AVSSs) for maintaining vehicle stability and maneuverability during emergency braking An approach for wheel slip prediction is proposed in this paper, which involves Auto-Regressive (AR) Time-Series modelling of longitudinal vehicle acceleration. This technique allows the usage of linear longitudinal vehicle dynamics for wheel slip estimation. A wheel slip prediction model was developed considering measurements from accelerometer and wheel speed sensor. This modified the Model Predictive Control (MPC) formulation to a univariate control input problem, involving braking torque. The objective function was devised for solving a least-squares reference tracking problem. An analytical solution for the MPC optimization problem was derived and implemented towards WSR. The proposed framework was programmed in MATLAB Simulink ® and co-simulated with IPG TruckMaker ® (a vehicle dynamic simulation software). The algorithm was tested in a Hardware-in-Loop (HiL) setup consisting of a pneumatic air brake system interfaced with IPG TruckMaker ® . Open loop studies from HiL led to the inclusion of Kalman filter for estimate tuning and PID inner loop control for brake pressure transients, which improved wheel slip regulation.

Wheel lock is an undesired phenomenon in Heavy Commercial Road Vehicles (HCRVs) and wheel slip control within a desired range is of crucial importance for stable and effective braking. This study proposes a framework to distribute brake force dynamically between the front and rear wheels, primarily to avoid instability by preventing wheel lock. Further, it ensures the maximum utilization of the available traction force at the tire-road interface that varies during the course of braking due to factors like load transfer. Wheel slip regulation provides an approach to maximize braking performance that subsumes the effects of varying road, load and braking conditions that occur during vehicle deceleration. The methodology proposed consists of a wheel slip controller that calculates the required brake force distribution parameters, which are then provided to the brake controller for control action. Sliding mode control was used because of the nonlinear nature of the longitudinal vehicle dynamic model considered and for robustness towards different parameter variations. The algorithm was implemented on a Hardware-in-Loop test setup consisting of a pneumatic air brake system, interfaced with IPG-TruckMaker ® (a vehicle dynamic simulation software), and co-simulated with MATLAB-Simulink ® . It was found that this algorithm improved the braking performance of a HCRV both in terms of stopping distance and vehicle stability.

This work proposes a method to simulate wheel lock of a Heavy Commercial Road Vehicle (HCRV) using pneumatic brake circuit on a brake dynamometer. The proposed methodology lumps the effects of wheel slip and load transfer during straight-line braking into ‘equivalent inertia’ on the wheels. This inertia profile could then be imported on a dynamometer interface and realized using suitable inertia discs and an electric motor. Equivalent inertia was computed from test datasets obtained from a Hardware-in-Loop (HiL) experimental system consisting of an air brake system and IPG TruckMaker ® , a vehicle dynamic simulation software. These datasets were obtained for various road, vehicle load and braking conditions. This framework would facilitate the evaluation of wheel slip regulation algorithms using a brake dynamometer by capturing necessary dynamics of HCRVs during braking. It is expected that such testing can be placed between HiL and on-road tests, and would provide greater confidence in Active Safety Systems (ASSs) before their deployment on vehicles.

This paper deals with tracking of desired yaw rate generated by the path planner of an Autonomous Ground Vehicle (AGV) in the presence of unmodeled dynamics, changes in operating conditions and parametric uncertainties. A mathematical model considering the dynamics of the test vehicle and the steering actuator was used for controller design. The estimate of the unknown part of dynamics, called the total disturbance, obtained from the Extended State Observer (ESO) was used by Sliding Mode Controller (SMC) to compensate the actual total disturbance. It was observed that the lower bound on the SMC switching gain depends on the ratio of total disturbance estimation error and assumed known part of the system dynamics. This allows the choice of a low value of SMC switching gain, which in turn resulted in reduced chattering amplitude. Further attenuation in chattering was achieved using a saturation function. After simulating the designed controller in MATLAB-SIMULINK environment, the controller was validated in IPG: CarMaker ® simulation platform over a large operating range by changing the mass distribution of the vehicle, speed of the vehicle, cornering stiffness of the tire and terrain friction coefficient. A look-up table was formulated for the maximum achievable yaw rate at different speeds, i.e., from 5 to 20 m/s, given the maximum steering angle input considering rollover and slip threshold while the terrain friction coefficient was also varied from 0.2 to 0.8. It was observed that the designed controller was robust to changes in operating conditions, parametric uncertainties and unmodeled dynamics.

The gradual decline of oil reserves and the increasing demand for energy have resulted in automotive manufacturers developing new environmentally friendly vehicles such as electric and hybrid vehicles. Selection of the correct hybrid configuration for a given driving condition is very important since it affects the performance of the vehicle and its fuel economy. This paper focuses on a detailed parametric analysis of a Series Hybrid Electric vehicle (SHEV). The objective of this paper was to develop a SHEV powertrain by initial parameter matching and component sizing, followed by its optimization for given design constraints. This involved study and calculation of components power specifications based on vehicle dynamics. Initial parameterization was followed by optimization to meet the design objective. The simulation of the optimized SHEV was done in the software ADVISOR for an Indian driving cycle (IDC). Based on the simulation results, an optimum range of the powertrain components was established.

Regenerative braking is applied only at the driven wheels in electric and hybrid vehicles. The presence of brake force only at the driven wheels reduces the lateral traction limit of the corresponding tires. This impacts the vehicle lateral response, particularly while applying the regenerative brake in a turn. In this paper, a detailed study was made on the impact of regenerative brake on the vehicle lateral response in front wheel drive and rear wheel drive configurations on dry and wet asphalt road surfaces. Simulations were done considering a typical set of vehicle parameters with the IPG CarMaker ® software for different drive conditions and braking configurations along the same reference track. The steering wheel angle, yaw rate, lateral acceleration, vehicle slip angle, and tire forces were obtained. Further, they were compared against the conventional all wheel friction brake configuration. The regenerative braking configuration that had the most impact on vehicle lateral response was analyzed and response variations were quantified.

In this paper, a collision avoidance algorithm (CAA) has been proposed using variable time headway considering heterogeneous traffic. The time headway used in the proposed CAA was tuned based on the traffic scenarios, the host vehicle’s load conditions and the type of the lead vehicle that the host vehicle encounters in the traffic. The proposed variable time headway would help to avoid the intervention of the collision avoidance system during normal driving and gain driver’s acceptance. The CAA was evaluated using a hardware-in-the-loop (HiL) experimental set-up integrated with the vehicle dynamic simulation software IPG/TruckMaker ® for different categories of lead vehicles such as 2/3 wheelers, passenger cars, light commercial road vehicles (LCVs) and heavy commercial road vehicles (HCVs). From the results, it was observed that while following a HCV, a smaller time headway was sufficient to prevent a collision compared to following a passenger car, LCV and 2/3 wheeler.

Even if there are many software and mathematical models available in the literature to analyze the dynamic performance of Unmanned Ground Vehicles (UGVs), it is always difficult to identify or collect the required vehicle parameters from the vehicle manufacturer for simulation. In analyzing the vehicle handling performance, a difficult and complex task is to use an appropriate tire model that can accurately characterize the ground-wheel interaction. Though, the well-known ‘Magic Formula’ is widely used for this purpose, it requires expensive test equipment to estimate the Magic Formula coefficients. The design of longitudinal and lateral controllers plays a significant role in path tracking of an UGV. Though the speed of the vehicle may remain almost constant in most of the maneuvers such as lane change, Double Lane Change (DLC), step steer, cornering, etc., design of the lateral controller is always a challenging task as it depends on the vehicle parameters, road information and also on the steering actuator dynamics. Although a mathematical model is an abstraction of the actual system, the controller is designed based on this model and then deployed on the real system. In this paper, a realistic mathematical model of the vehicle considering the steering actuator dynamics has been developed by calculating the cornering stiffnesses from the basic tire information and the vertical load on each tire. A heading angle controller of the UGV has been considered using the Point-to-Point navigation algorithm. Then, these controllers have been implemented on a test platform equipped with an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS). A wide range of experiments such as J-Turn, lane change and DLC have also been conducted for comparison with the simulation results. Sensitivity analysis has been carried out to check the robustness and stability of the controller by varying the cornering stiffness of tires, the most uncertain parameter. The longitudinal speed of the vehicle is assumed to vary between a minimum value of 1.4 m/s and a maximum value of 20 m/s. It has been found that when the vehicle is moving at a constant velocity of 3.2 m/s, a heading angle change of 20 degrees can be achieved within 3 seconds with 2% steady state error using a proportional controller. It was observed that at lower speeds, the controller is more sensitive to the steering actuator dynamics and at higher speeds, the controller is more sensitive to the cornering stiffness of tires.

Diesel engines require atomized fuel injection inside the combustion chamber for better combustion and reduced emissions, which in turn requires a common rail fuel injection system with higher operating pressure capabilities. But, these requirements lead to increased fuel leakage through the working clearance in the pump to the engine lubrication oil chamber and increased lubrication oil leakage to the fuel side of the pump. The fuel leakage to lubrication oil (FtO) affects the lubrication property of the oil, which in turn affects the life of the lubricated components in the engine. The lubrication oil leakage to fuel (OtF) increases the injector nozzle coking and emission. The leakage flow through the clearance gap was generally studied for 1-dimensional cases by using the Couette–Poiseuille equation obtained from the continuity and the incompressible Navier–Stokes equation. The existing analytical approaches do not consider the fluid interactions/mixing in the 2-dimensional domain. The same is addressed in this study using the numerical simulation tool, Ansys CFX, to estimate the volume flow rate of OtF and FtO considering various design parameters such as diametrical clearance (4–6 μm), cylinder bore taper and piston speed. The leakage of fuel and lubrication oil take place between the working clearance of the piston and the cylinder bore. Pressure and drag effects are two important mechanisms that drive the leakage flow. The transient piston wall speed and the transient pressure at fuel side and lubrication oil side were used as the inputs to the simulation. The grid sensitivity analysis using different grid sizes was done to optimize the grid size. Higher computation time and memory for simulation work was reduced by optimizing the various simulation input parameters. The benchmark problem of Couette-Poiseuille flow was solved and the results were cross-checked with the analytical results. The actual two dimensional flow domain was modeled for the simulation of fluid flow with mixing. The mass and volume flow rate of lubrication oil and fuel were captured at the specified boundary with respect to time. The simulation was carried for various clearance values, clearance taper and speed ranges. The OtF and FtO were found to be increasing with respect to increase in clearance and speed. With this analysis, the sensitivity of the leakage flow rate of fuel and lubrication oil with respect to the important parameters was observed.

Electric and hybrid vehicles are emerging rapidly in the automotive market as alternatives to the traditional Internal Combustion Engine (ICE) driven vehicles to meet stringent emission standards, environmental and energy concerns. Recently, Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs) have been introduced in many countries including India. One configuration of a HEV is the Series Hybrid Electric Vehicle (SHEV). The design and analysis of the drive system of a SHEV under Indian conditions is the focus of this paper. In conventional vehicles, the ICE is the power source that drives the vehicle. The energy from the ICE is distributed to the wheels through the transmission, which is then used to generate the traction force at the tyre-road interface. In a HEV, both the engine and the electric motor provide the energy to drive the vehicle. In a SHEV, the energy generated by the electric motor is transmitted through the transmission to meet the torque demand at the wheels. Based on the driver’s acceleration demand and the state of charge of the battery, the controller manages the ICE, the generator and the battery to supply the required energy to the motor. The motor finally develops the required drive torque to generate the traction force at the wheels to meet the vehicle drive performance requirements like gradeability, acceleration and maximum speed. The objective of this paper is to discuss the design of the drive system of a SHEV. This involves the calculation of the power specifications of the electric motor based on the vehicle drive performance requirements. The equations for performing these calculations are presented. The procedure is then demonstrated by considering a typical Indian commercial vehicle along with its typical vehicle parameter values. A simulation study has also been performed by considering the Indian drive cycle to demonstrate the energy savings obtained by the use of a SHEV.