The piston temperature is usually measured by a hardness plug. The principle is to use a special alloy to produce a permanent hardness change plug after quenching. The surface hardness varies with tempering temperatures. The measurement is done in combination with a hardness tester and other equipment [3]. For the material of the hardness plug, the tempering temperature and hardness change are preferably linear to linear. The material used in this experiment was GCr15 ball bearing steel, and the experimental instrument was a digital micro Vickers hardness tester. For the instrument to work properly, the measuring range was set to 5 HV to 3000 HV, the minimum detection unit was 0.025 μm, the applied load was 300 N, and the load holding time was 10 s [4]. After quenching, 10 hardness plugs are taken for hardness measurement, and 3 measurement points were taken on each hardness plug. The measured data was shown in Table 1 and Fig. 1.

From the preceding data, it can be found that the hardness plug after quenching had very uniform hardness values, with a deviation within ±10 HV, and the hardness of the experimental material met the requirements of HV ≥ 800.

The tempering test were carried out in the hardness plug tempering test in a constant temperature box, and the temperature was kept at 150°C to 450°C every 50°C for 2 h (the engine piston temperature was between 250°C and 300°C, and the measurement point was increased by 275°C within this range), with air-cooled in the furnace. The measured data was shown in Table 2.

According to the data in Table 2, a characteristic curve of hardness-tempering temperature was drawn, as shown in Fig. 2. It can be seen from Fig. 2 and Table 3 that the change basically met the requirements of a linear change and the characteristic was relatively good.

The main parameters of the piston were shown in Table 4. In order to ensure the accuracy of the experimental measurement, 20 measurement points were selected, and the hardness plug was installed according to the piston solution structure, shown in Fig. 3.

The engine experiment of the piston temperature test was accomplished under certain conditions. The main parameters of the test conditions were shown in Table 5.

The temperature data under different working conditions between original piston and anodized piston was shown in the Figs. 4 and 5. It can be seen from the that under the conditions of maximum operating torque (as short for T_tpmax) and maximum operating power (as short for P_emax), most of the temperature values of the anodized piston were lower than those of the original piston, which indicated that the above process improvement had the effect of reducing the thermal load of the actual work of the piston.

The piston material was forged aluminum 2A80, the density was 2.77 * 10^3 kg/m³, the elastic modulus of its material properties was 72 Gpa, the Poisson’s ratio was 0.33, and the tensile strength was 375 Mpa. The thermal conductivity and linear expansion coefficient were shown in Table 6.

The finite element analysis software of this time was ABAQUS, which was mainly considered to be a set of powerful engineering simulation finite element software, which can solve problems of not only relatively simple linear analysis but also many complex nonlinear problems [5]. The finite element mesh model of the piston was shown in Fig. 6. The piston model used in this calculation was a second-order tetrahedral mesh cell in compliance with the requirements of finite element analysis. The finite element parameter information contained 91517 nodes and 53440 elements.

Figs. 9 and 12 illustrated the comparison curves between computer simulation and experiment under different working conditions. It can be seen from Figs. 9 to 12 that computer simulation was in highly agreement with the experimental data, and the error rate was less than 5%, which effectively validated the conclusion that the least squares method and the computer simulation have certain reliability and meet the requirements of engineering applications. It is quite normal for the difference between experiment and simulation. The possible reasons for the difference included the unstable test conditions, inaccurate experimental data, differences in boundary conditions measurement error and so on. However, from Fig. 11, it can be inferred that the change trend of experiment and simulation had a high degree of consistency, which reflected from the other side that the simulation had a certain credibility.

Through computer simulation analysis of the piston temperature field data, as shown in Figs. 13–16 above, it can be seen that under the maximum torque condition, the temperature after optimization was 265.3°C, which was 51.9°C lower than the temperature before optimization (317.2°C), and the decrease rate was 16.36%. Under the maximum power condition, the temperature after optimization is 290.9°C, which was 16.6°C lower than the temperature before optimization (307.5°C), and the decrease rate was 5.4%. From the above simulation, it can be seen that by using the anodizing process, the maximum temperature of the piston can be reduced effectively no matter it is the maximum torque condition or the maximum power condition.

To meet the strength requirements of the material at high temperature, the thermal stress of the piston temperature field before and after optimization should be within 50 Mpa [11]. Figs. 17 to 20 had be shown the thermal stress analysis result between the original piston and the anodized piston under two different conditions. It can be seen from the cloud diagram that under either the T_tqmax condition or the p_emax condition, the large thermal stress of the region after optimization was significantly reduced compared with before optimization, especially at the top inside the piston.