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As the FTP-75 drive cycle does not have a prescribed gear shift pattern, automotive OEMs have the flexibility to design. Conventionally, gear shift pattern was formulated based on trial and error method, typically with 10 to 12 iterations on chassis dynamometer. It was a time consuming (i.e. ~ 3 to 4 months) and expensive process. This approach led to declaring poor fuel economy (FE). A simulation procedure was required to generate a gear shift pattern that gives optimal trade-off amongst conflicting objectives (FE, performance and emissions). As a result, a simulation tool was developed in MATLAB to generate an optimum gear shift pattern. Three different SUV/UV models were used as test vehicles in this study. Chassis dyno testing was conducted, and data was collected using the base and optimized gear shift patterns. Dyno test results with optimized gear shift pattern showed FE improvement of ~ 4 to 5% while retaining the NOx margin well above engineering targets.

Determination of vehicle specifications (for example, powertrain sizing) is one of the fundamental steps in any new vehicle development process. The vehicle system engineer needs to select an optimum combination of vehicle, engine and transmission characteristics based on the product requirements received from Product Planning (PP) and Marketing teams during concept phase of any vehicle program. This process is generally iterative and requires subject matter expertise. For example, accurate powertrain sizing is essential to meet the required fuel economy (FE), performance and emission targets for different vehicle configurations. This paper analyzes existing vehicle specifications (Passenger Cars/SUVs - Gasoline/Diesel) in different automotive markets (India, Europe, US, Japan) and aims to determine underlying trends across them.

Objective metrics for performance evaluation of ride, handling and steering are required to compare, validate and optimize dynamic behavior of vehicles. Some of these objective metrics are recommended and defined by International Organization for Standardization (ISO) and Society of Automotive Engineers (SAE), which involve data processing, statistical analysis and complex mathematical operations on acquired data through simulation or experimental testing. Due to the complexity of operations and volume of data, evaluation is often time consuming and tedious. Process automation using existing tools such as MS Excel, nCode, Siemens LMS, etc. includes several limitations and challenges, which make it cumbersome to implement. This work is about development of a centralized platform for quantification, visualization and comparison of ride, handling and steering performance metrics obtained from testing and simulation data as per relevant ISO standards.

Ride is essentially the outcome of coupled dynamics of various involved sub-systems which make it too complex to deal analytically. Tires, amongst these, are known to be highly nonlinear compliant systems. Selection of tires specifications such as rated tyre pressure, etc. are generally decided through subjective assessment. While experts agree that tyre pressure affects the attributes such as ride to a noticeable degree, the quantification of the change often remains missing. In the current work, vibration levels of various sub-systems relevant to ride in an SUV are measured for three different tyre pressures at different speeds over the three randomly generated roads. For the purpose, artificial road profiles of classes A, B and C are synthesized from the spectrum of road classes defined in ISO 8608:2016 and reproduced on a four-poster test rig.

Across the automotive industries, objective measurements and subjective assessment of vehicle ride performance are routinely carried out during development as well as validation phase. Objective measurements are receiving increased attention as they are generally believed to offer a higher degree of objectivity and repeatability compared to the subjective assessment alone. Typical industry practices include the acquisition of vehicle-occupant vibrational response on specified road sections, test surfaces on proving grounds or in a controlled input environment such as four-poster test rig. In presented work, a study is performed on the repeatability of vehicle ride performance metrics such as weighted RMS acceleration and frequency responses using the data acquired in repeated trials conducted using three different sports utility vehicles (SUVs) on a sufficiently long designated road section.

Vehicle lateral dynamic response parameters such as yaw velocity, lateral acceleration, roll angle, etc. depend on the nature of steering input. Response parameters vary with the amplitude and frequency of steering input. This paper deals with developing insights into the effect of steering input frequency on transient handling dynamics. For the purpose two SUV segment vehicles with similar curb weight are considered. Vehicles are given pulse inputs of the amplitudes corresponding to 4 m/s2 steady state lateral acceleration and target speeds of 80 kmph and 100 kmph, as recommended in ISO 7401:2011. Steering inputs are executed using a Steering Robot (ABD SR30). Lateral transient dynamic response gains as well as natural frequencies of yaw are studied for 0-2 Hz input frequencies. Several insights are developed, adding to the understanding of transient lateral dynamics and its relationship with steering input.

Poor clutch life is a major issue for some light commercial vehicle models. Clutch overheating is the primary cause for clutch failure. Some of the reasons include inappropriate gear selection by the driver, poor low-end dynamic torque availability from an engine, heavy stop and go traffic, vehicle overloading resulting in excessive clutch slippage especially in gradients, riding of the clutch pedal by the customer etc. These situations lead to a high thermal energy dissipation at the clutch, increasing clutch wear and in extreme conditions leading to not only poor shift quality but also eventual clutch failure. Unfortunately, it is not practical to monitor clutch temperature in a production vehicle due to high costs or technical challenges involved. This paper describes 1-D thermal modeling of single plate dry clutch typically used in passenger car/truck and bus applications. The objective of simulation is to estimate the temperature rise on the clutch facing and clutch housing.

Each OEM has a distinguishing drivability character that defines its image in the market to achieve brand differentiation. Drivability is one of the important factors along with fuel economy that determines the success of a vehicle vis-à-vis its competitors. It can be said that the need for good drivability among customers is increasing day by day similar to the need for high fuel economy. Drivability is the response that a vehicle delivers to the inputs of the driver which are mainly accelerator, brake, clutch, gear and steering. The dynamic response of the vehicle is mainly in terms of velocity and acceleration. The way the response is delivered will characterize the drivability of a vehicle. The drivability event discussed in this paper is throttle tip-in response which is one of the critical evaluation factors for defining the character of a Sports Utility Vehicle.